PRAISE FOR

THE FOUR PILLARS of INVESTING

When it comes to investing, risk control matters far more than chasing returns. In this book Dr. Bill Bernstein will show you that you have probably been worrying about the wrong risks when it comes to your investments. When you understand the theory, history, psychology, and business of investing, you will be far more likely to successfully reach your own financial goals, while taking as little real risk as necessary.

—James M. Dahle, MD

founder of The White Coat Investor

Bill Bernstein possesses a rare combination of gifts: mathematician, historian, statistician, psychologist, econometrician, and wordsmith. These and a profound sense of what financial truths are misunderstood, crucial, and captivating form the foundation for this welcome edition of The Four Pillars of Investing, a pillar of my investment strategies course.

—Edward Tower

economics professor, Duke University

Successful investing is a mind game. You win by understanding and controlling risk, not by plunging into the financial jungle in search of a unicorn. Your goal is a comfortable life, a well-funded retirement, and, perhaps, legacies for your children. This valuable book shows you how to keep your eye on the ball—earning capital returns the intelligent way.

—Jane Bryant Quinn

author of How to Make Your Money Last: The Indispensable Retirement Guide

In this fully revised investment classic, you can learn the lessons of a lifetime from one of America’s most preeminent investment advisors. Writing in an engaging and humorous style, Bernstein teaches us that successful investing involves not only doing the right thing but also avoiding the all-too-common blunders that can ruin any investment plan. Incorporating lessons from investment theory and history and understanding our psychological biases, this wise and entertaining book provides a trusted source of investment advice.

—Burton G. Malkiel

economics professor, Princeton University, and author of A Random Walk Down Wall Street, 50th Anniversary Edition, 2023

Bernstein has brilliantly distilled what is essentially four books into one here in an enlightening tour through investing theory, history, psychology, and business using practical examples, stories, metaphors, math, and a bit of humor. It’s full of hard-won investing perspective and sage advice in an easily digestible format—the kind of book you could recommend to someone new to investing and know you did them right.

—Eric Balchunas

analyst, Bloomberg, and author of The Bogle Effect

Four Pillars has something for everybody. It’s the first investment book you should read, and also the fiftieth. Few investment books appeal to both novices and experts, and even fewer are a joy to read while doing so. It’s approachable for novices, a revelation to apprentices, and instructive even for experts.

—John Rekenthaler

director of research, Morningstar

Also by William Bernstein

The Intelligent Asset Allocator

The Birth of Plenty

A Splendid Exchange

The Investor’s Manifesto

Rational Expectations

Masters of the Word

The Delusions of Crowds

Copyright © 2023, 2003 by McGraw Hill. All rights reserved. Except as permitted under the Copyright Act of 1976, no part of this publication may be reproduced or distributed in any form or by any means, or stored in a database or retrieval system, without the prior written permission of publisher.

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Library of Congress Cataloging-in-Publication Data

Names: Bernstein, William J., author.

Title: The four pillars of investing : lessons for building a winning portfolio / William Bernstein.

Description: Second edition. | New York, NY : McGraw Hill, [2023] | Includes bibliographical references and index.

Identifiers: LCCN 2023003755 (print) | LCCN 2023003756 (ebook) | ISBN 9781264715916 (hardback) | ISBN 9781264716425 (ebook)

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FOREWORD

By Jonathan Clements

Risk Is a Many-Splendored Thing wasn’t a 1955 hit song by the Four Aces or an award-winning movie starring William Holden and Jennifer Jones. Which is a shame.

Bill’s book, on the other hand, is indeed about risk in all its many facets. “What,” you cry, “are you telling me the pages ahead won’t show me how to pick investments that’ll make me Rockefeller rich?”

Rockefeller rich might be overpromising, but rich is certainly a possibility. Here’s the thing that every investor needs to grasp: the road to investment wealth isn’t a direct one. We won’t get there by scanning the shelves of Wall Street merchandise and asking the obvious question, “Which of these turkeys is going to fly?”

This, of course, is the question we all ask when we first start investing. We scour lists of hot mutual funds and sizzling stocks. We study market trends and try to divine which will be our friend. We use every trick in the book to find investments that’ll make us obscenely wealthy. Along the way, mostly what we find is that we’re embarrassingly clueless.

Many folks, alas, never learn the error of their ways, instead spending their financial life bouncing from one failed investment scheme to the next. But thoughtful investors eventually realize that they need to give up chasing performance and start managing risk—and that, ironically, is when their investment results get a whole lot better.

But which risks should we manage? This, I believe, is the true genius of Bill’s book, which was first published two decades ago and is now widely considered to be an investment classic. In words any educated adult can understand, Bill describes the potholes that can derail our financial journey.

Those potholes include—and this is only a partial list—such things as deflation, buying investments with borrowed money, miserably low long-run stock and bond returns, confiscation of assets, chasing past performance, overestimating our risk tolerance, vicious stock market declines, stockbrokers, skewness, our own gross overconfidence, rotten investment results early in retirement, soaring inflation, and watching cable financial news.

Sound like a treacherous world? It is—and it isn’t. There are countless ways to lose great gobs of money in the financial markets. But, as Bill explains in the pages ahead, these losses can typically be sidestepped or made bearable with the right mix of discipline and knowledge. That discipline and knowledge can be obtained by studying Bill’s four pillars of money-management wisdom: investment theory, financial history, investment psychology, and the business of investing.

Looking to launch a prudent investment life or double-check you’re still on the right track? You’d be hard-pressed to find a financial guide that’s wiser and more entertaining than Bill’s The Four Pillars of Investing. But before I step out of the way so you can delight in the pages that follow, let me highlight a few ideas that both Bill and I embrace. As you think about the risks you’re taking with your portfolio—and, indeed, with your broader financial life—I’d encourage you to pay particular attention to two key notions.

First, more things can happen than will happen. We all know the future is uncertain. But to preserve our sanity and avoid sleepless nights, we tend to downplay how much uncertainty exists. We assume that next year will look a lot like this year, that we’ll go to bed in the same house, that our spouse will still be there next to us, snoring merrily, and that we’ll get up in the morning and head to the same job. Similarly, we assume that today’s dominant trends in the economy and the financial markets will continue to prevail.

A brief tour through economic and market history, coupled with a quick review of past turmoil in our own lives, suggests that such assumptions are questionable at best. I’m not advocating that we spend our days on pins and needles, braced for the next round of chaos. But at the same time, we shouldn’t be too bold in our financial decisions, because such overconfidence can come back to haunt us. Yes, by all means, maintain an unwavering commitment to core financial principles—saving diligently, managing risk, holding down investment costs, limiting taxes, and so on. But when it comes to our assumptions about the financial future, we should think like a serial philanderer and never grow too attached to any of them.

Second, we get just one shot at making the financial journey from here to retirement—and we can’t afford to fail. The implication: we need to think hard about potential financial consequences. All this can be captured by one simple question: What if I’m wrong?

For instance, what if I stick solely with US stocks, and they endure a three-plus-decade bear market, just like Japan? What if I put off saving for retirement until my final 20 years in the workforce, and those years are marked by layoffs and long periods of unemployment? What if my retirement doesn’t last the 30 years that I’m expecting, but rather 40 or 50 years?

Managing risk can be tricky, not least because we’re human. We struggle to imagine all the bad things that can happen, and we imagine that we know things about the future that simply can’t be known. With every fiber of our being, we resist accepting uncertainty and our own lack of prescience.

But if we do indeed accept those two realities, the benefits for our investment performance—and our own sense of well-being—can be remarkable. Instead of thrashing around, with our investments and our mental state constantly whipsawed by the financial markets, we can design a portfolio that should fare reasonably well, no matter what the future throws at us. We can save and invest in such a way that we know we’ll survive financially—and hopefully thrive—in almost any economic environment. Trust me: the sense of financial security and serenity that comes with that knowledge will leave you happier than almost anything else that money can buy.

ACKNOWLEDGMENTS

This book covers too many areas—financial theory, financial history, psychology, and the nuts and bolts of the investment business—for anyone’s expertise to fully cover the ground.

I’d like to thank the following individuals for their expert help: Amy Arnott for fund flow and returns data, Christine Benz on target-date funds, Jane Bryant Quinn on financial journalism, Ilia Dichev on the “other side” of the dollar/time-weighted gap, Martin Fridson on high-yield bond defaults, Paul Hyams and Jane Lockshin for background on the remarkable story of Sylvia Bloom, Antti Ilmanen on (low) expected returns, Mike Nolan on aggregate fund data, Wade Pfau on annuities and the life cycle, Craig Rowland on foreign asset custody, Denise Schmandt-Besserat for image help, Dan Solin on brokerage practices, Richard Sylla on the concept of “unimpaired capital,” and Greg Zuckerman on D. E. Shaw and James Simons.

Mike Piper provided invaluable assistance on deferred annuities, Rick Ferri helped me sort out multiple issues regarding ETFs, and Allan Roth responded to my nearly incessant pestering about both these areas. Special thanks goes to Jason Zweig, who has over the years taught me much about market history and neuropsychology.

Jim Dahle, John Rekenthaler, Jonathan Clements, and my estimable business partner, Susan Sharin, provided me with the benefit of their aggregate century’s experience in the investment world and reviewed both the content and style of this manuscript. I’ll happily take full credit for any remaining errors.

Thanks go to Steve Straus, Maki Wiering, Ingrid Case, and Pattie Amoroso for deftly guiding the book’s production through to completion, and particularly to Judith Newlin, who was not only involved in the project from the first drafts to the final galleys, but who also graciously responded to a near continuous stream of questions and issues from me.

Finally, as always, the alchemical literary skills of my dear wife, Jane, turned the unformed blob of my rough prose, sentence by sentence, into copy that I could unashamedly show to others. I would be lost without her.

INTRODUCTION

THE HIGHWAY OF RICHES

The year 1998 saw one of the most spectacular falls from grace in the long and sordid history of high finance: the failure of Long-Term Capital Management (LTCM).

The hedge fund, founded four years prior by legendary Salomon Brothers executive John Meriwether, featured Wall Street’s best and brightest. Heading the list were two Nobel Prize winners: Myron Scholes and Robert C. Merton, the inventors of a groundbreaking theory of option pricing.

In the late 1990s, the firm enacted a financial tragedy worthy of Icarus. LTCM’s blindingly complex derivatives-based trading strategy was leveraged 25 to 1 with borrowed funds; it quadrupled investors’ money over a four-year period before it imploded.¹

Over a much longer time span, an unassuming legal secretary named Sylvia Bloom succeeded where LTCM had failed. She began her working life at a New York law firm in 1947 and stayed there until 2014—an astounding 67 years. She died a few years later, just shy of her ninety-ninth birthday.

The executor of Bloom’s estate, her niece Jane Lockshin, could not believe her eyes: its assets were worth more than $9 million, consisting mainly of common stocks. Two-thirds went to the Henry Street Settlement, the largest bequest the storied Lower East Side social service charity had ever received. No one, not even her late husband, a retired firefighter, was aware of her wealth. Ms. Lockshin regularly took her aunt out to lunch and, as one does for an elderly relative, always paid the bill.

How had a secretary succeeded where the luminaries at LTCM had failed? Bloom did so for three reasons. First, she did not invest with borrowed money—that is, she did not employ leverage, let alone at LTCM’s stratospheric 25:1 ratio. At that level, a mere 4% fall in asset prices would bankrupt the fund. The firm’s mathematical models, based on historical data, told LTCM that the value of their holdings would never fall this much. The models could not have been more wrong. The most brilliant minds in finance forgot the bald fact that with alarming frequency the markets go barking mad and obliterate previously well-established relationships among asset prices.

Second, Bloom had time on her side—decade upon decade of it. An apocryphal quote often attributed to Albert Einstein has it that “Compound interest is the eighth wonder of the world. He who understands it, earns it. He who doesn’t, pays it.” Sylvia Bloom had it, in spades.

Unlike the geniuses at LTCM, she wasn’t trying to get rich quick, but rather to get rich slow—a much safer bet. Bloom could turn a secretary’s stream of savings into millions because her strategy allowed the magic of compound interest to motor away for 67 long years; LTCM’s lasted barely 4 years. If compounding is indeed the eighth wonder of the world, then the worst thing one can do is to cut it short with dumb stuff: leverage, chasing star money managers, overestimating risk tolerance, and watching financial cable shows, to name just a few things.

Ms. Bloom’s third advantage was her frugality. She certainly didn’t deprive herself; she dressed well, occasionally sported a fur coat, and traveled frequently with her husband. But when the Twin Towers came down on 9/11, the 84-year-old secretary walked across the Brooklyn Bridge and took the bus home. Just before she retired, a coworker and close friend, Paul Hyams, spied her climbing out of the subway during a blinding snowstorm and asked her what she was doing there, to which she replied, “Why, where should I be?”² Had she lived more lavishly, she wouldn’t have left such a large estate. One saves in order to spend later—in Bloom’s case, on charity, not on herself.

Investing, distilled to its essence, is the conveyance of assets from your present self to your future self. Alas, the financial highway between those two different people is strewn with black ice and massive potholes. At the risk of further torturing the highway metaphor, the average portfolio’s lifetime route also winds through two or three of the financial world’s versions of treacherous mountain passes with no guardrails—the brutal bear markets that accompany financial panics.

Manifestly, the more slowly you drive, the more likely your assets are to arrive safely at your destination. This is what Bloom did with her money; LTCM’s principals, to their and their investors’ detriment, put the pedal to the metal. Warren Buffett, as he so often does, put it most succinctly: “To make money they didn’t have and didn’t need, they risked what they did have and did need.”³

Simply put, Bloom succeeded because her strategy survived, and LTCM’s didn’t because their strategy “risked out.” Finance professionals and academics often deem a portfolio that’s light on stocks suboptimal, but a “suboptimal” strategy that survives fear and panic, or better yet, doesn’t produce it, is preferable to an optimal one that takes on unnecessary risk.

Speaking about geopolitics, author and historian Robert Kaplan observed that “half of everything is geography; the other half is Shakespeare.” In the same way, one can say that investing is half math and half Shakespeare. There’s the essential but dry, Mr. Spock/mathematical part of finance, but also its human half: the abject fear that suffuses bear markets, our empathy and tendency to imitate and channel the fear and greed of others, and to privilege narratives over data and facts. Often, investing’s math and Shakespeare are diametrically opposed, and if you don’t master the Shakespeare, all the math in the world isn’t going to help you. In other words, the Shakespeare is not the art and poetry of investing, but rather its Hamlet, Lear, and Macbeth—the all too human irrationality as expressed in human endeavor and by the cruel mistress of history.⁴

How, then, does the individual investor master both the math and Shakespeare of the craft and avoid the dumb stuff that will send their magically compounding investment vehicle skidding off the highway of riches? By mastering the Four Pillars of Investing.

PILLAR ONE: INVESTMENT THEORY

If you learn nothing else from this book, it should be this: risk and return go hand in hand. Do not expect high returns without experiencing occasional bone-crushing losses. As too many learned to their chagrin during the internet bubble of the late 1990s, a stock that increases by 900% one year can just as easily fall 90% the next. There is no way of avoiding the risks that come with common stocks, and as we’ll soon see, there is no market timing fairy who can reliably tell you when to get out of the stock market. At any given moment, market Cassandras abound, and in every crash, purely by chance, one or two will time that call perfectly. But almost like clockwork, the subsequent predictions of these geniuses fare worse than a coin flip. And even if you manage to sell at just the right time, you still have to guess right a second time about when to get back in. Consider: from the market peak in late 2007 until its low in early March 2009, an investment in the S&P 500 fell by 55.2% (including dividends). By the end of 2022, it had gained 644% from that low point.⁵

Such losses are the ticket price for the theater of stock market returns. John Maynard Keynes put it best when he opined:

I do not think it is the business, far less the duty, of an institutional or any other serious investor to be constantly considering whether he should cut and run on a falling market, or to feel himself open to blame if shares depreciate on his hands. I would go much further than that. I should say that it is from time to time the duty of the serious investor to accept the depreciation of his holdings with equanimity and without reproaching himself.⁶ (italics added)

The key word in the preceding quote is “equanimity”: the ability to bear losses calmly and as an ordinary matter of course. One of this book’s most important investment secrets is that the most potent elixir of financial equanimity is a large pile of safe assets—in the case of the US investor, dull, low-yielding Treasury securities, which allow you to hold on when things look the darkest. They are, in this sense, in fact the highest-returning asset in your portfolio, a secret ignored by LTCM’s principals.

Over the past two decades my thoughts about life-cycle investing, particularly pertaining to the potentially devastating combined effects of low future stock and bond returns and sequence-of-returns risk—the possibility of an adverse initial returns draw early in retirement—have evolved. I’ve come to realize that the major determinants of stock risk are in fact the age of the investor and her “burn rate”: how much of her portfolio gets spent each year. Consequently, I’ve shifted the discussion of how to vary asset allocation throughout the life cycle toward the end of the “theory” section in Chapter 6.

PILLAR TWO: INVESTMENT HISTORY

Viewed over the decades and centuries, the capital markets seem as neat and tidy as an English aristocrat’s rose garden: stocks return more than bonds, which in turn return more than cash, all in an approximately predictable manner. But over periods as long as several years, the financial markets can go off the rails, as they did during the late 1990s, when companies needed only eyeballs and clicks—forget earnings and dividends—to command ionospheric prices, or the early 1930s, when the shares of some companies sold, incredibly, for less than the value of their cash on hand.

If you’ve seen the movie before, you’ll know how it ends. Were you transported back in time to a dinner party in 1999, topic A would have been the stupendous amounts of money being made by tech investors, and the easiest way to pick out who did and who didn’t get snookered would have been to administer a brief quiz on the 1929 crash: How was Goldman Sachs involved? Just who was Samuel Insull?

Finance is not a hard science like physics or engineering; rather, it’s a social science. The difference is this: a bridge, electrical circuit, or aircraft will always respond in exactly the same way to a given set of circumstances, while the financial markets do not, a hard fact that brought LTCM’s principals and clients to grief. The physician, physicist, or chemist who is unaware of their discipline’s history does not suffer greatly from the lack thereof; the investor who is unaware of financial history is irretrievably handicapped.

The successful investor needs familiarity with two historical concepts:

1.   The long-term returns and short-term volatilities of various asset classes

2.   How Mr. Market, as the legendary Benjamin Graham referred to the pullulating mass of investors, suffers from severe bipolar disorder, periodically swinging between extremes of euphoria and depression

PILLAR THREE: INVESTMENT PSYCHOLOGY

Our late-Pleistocene ancestors lived in a world where hair-trigger reactions to a dangerous environment meant life or death. Over at least the previous hundreds of thousands of years, our species evolved lightning-fast behaviors exquisitely adapted to that environment.

Just 300 generations after the end of the last ice age, we live in a financial world whose risk horizon is measured in decades, not seconds. Consequently, the investor’s greatest enemy is the Stone Age face staring back in the mirror.

Consider the skunk. Over millions of years, it evolved an effective strategy for dealing with large predators with sharp teeth: turn 180 degrees and spray. This response, alas, does not work as well for its modern descendants in a semi-urban environment, where the biggest threat is a multiton hunk of metal moving at 60 miles per hour.

Humans, then, are the investing equivalents of the modern skunk. Behavioral finance has received a lot of attention—perhaps a little too much—of late, but it still can teach us. The successful investor learns how to avoid the most common behavioral mistakes and to confront their own dysfunctional investment behavior. We’ll find that unsuccessful investors:

Images   Are grossly overconfident, not only about their ability to time the market and to pick stocks and successful asset managers, but even worse, about their risk tolerance.

Images   Overpay for certain classes of stocks.

Images   Trade too much, at great cost.

Images   Seek out financial choices that carry low probabilities of high payoffs, but have low long-term returns, such as IPOs and lottery tickets. One of the quickest ways to the poorhouse is to make finding the next Amazon.com your primary investing goal.

Learning how to deal with these foibles, among many others, pays a generous stream of dividends.

PILLAR FOUR: THE BUSINESS OF INVESTMENT

The prudent traveler stays away from war zones. It’s the same in finance. In fact, you won’t go far wrong by treating the entire financial services industry as a battlefield—certainly any stockbroker or full-service brokerage firm, any newsletter, any advisor who purchases individual securities, and any hedge fund. It’s not too much of an exaggeration to say that the average stockbroker services his clients in the same way that Baby Face Nelson serviced banks.

Many financial advisors and brokers, for example, are shockingly ignorant of the fundamentals of investment theory. The reason for this sorry state of affairs is simple: neither the industry nor the government imposes any educational requirements on brokers or financial advisors, or even on the managers of hedge, pension, or mutual funds, and the industry observes a moral code that would give the tobacco industry a run for its money.

In short, you are locked in a constant zero-sum battle with this behemoth. The good news is that with each passing year it becomes easier to tame the beast. When I published this book’s first edition two decades ago, there was only one safe place to shelter from it, and that was the Vanguard Group’s family of low-cost mutual funds. In the interim, several other major investment firms, having had their collective lunches eaten by Vanguard, decided that if they couldn’t beat it, they would join it. They began to offer a wide range of inexpensive mutual funds and ETFs, even Vanguard’s, on their own platforms. Meanwhile, Vanguard has become the victim of its own success and has poorly handled the flood of new customers. It remains a viable choice, but certainly now not the only one.

USING THE FOUR PILLARS

The book’s last section will translate the four pillars into the mechanics of designing and maintaining an efficient investment portfolio:

Images   Choosing which mutual funds and securities to employ

Images   Getting off dead center and building your portfolio

Images   Maintaining and adjusting your portfolio over the long haul

***

I’ve been writing about finance for the past quarter century, and I’ve learned a few things along the way. I initially approached the subject as a mathematical exercise: collect return series on various broad classes of stocks and bonds, select the mix that optimizes the trade-off between risk and return, then figure out how to deploy that mix through the selection of commercially available vehicles.

My first effort, The Intelligent Asset Allocator, initially published electronically in 1995, then later in hard copy by McGraw Hill, was mathematically dense—enough so that it appealed mainly to scientists and engineers, but not to many other readers. In the words of one of my friends, it was a “successful failure.” A few years later, I attempted to broaden my audience with the first edition of The Four Pillars of Investing, but only partially succeeded. My medical colleagues—certainly a well-educated and quantitatively competent bunch—still got cross-eyed from all the math.

Since I wrote this book’s last edition in 2002, a few things have changed. The most spectacular was the biggest financial crisis since the Great Depression, which roiled the world’s financial markets in 2007–2009, then echoed through Europe a few years later, followed by a global pandemic. Ironically, the remarkable decline in interest rates and resultant ballooning of stock markets that followed presented investors at the end of 2021 with one of the most daunting challenges in the history of finance: bloated asset prices with low expected returns, a phenomenon that was only partially attenuated by 2022’s carnage in both stocks and bonds.

Over a quarter century of writing about finance and history, I’ve learned that readers greatly prefer compelling narratives to data and math. With luck, this book’s critically important data can be cut up into easily digested morsels embedded within the book’s stories. The math cannot be so effortlessly processed, but fortunately the book can be understood without it. In order to avoid disappointing the minority of readers who actually enjoy all the numbers, I’ve segregated them into “math boxes” that the general reader can ignore.

Finally, my journey through finance in the two decades since this book’s first edition has taught me more than a few things:

Images   If you can’t save, it doesn’t matter how well you invest, and an understanding of money’s true utility determines how well you’re able to accumulate it. If you think that money’s purpose is to buy stuff, you are doomed to fail, since you’ll quickly find yourself trapped on the “hedonic treadmill,” the insidious evolving hunger for a yet more expensive car, a yet fancier house, or a yet more swish vacation. The best money in the world, if you’ll allow me the book’s only F-bomb, is “fuck-you money”: that used to buy time and autonomy.

Images   What one might call “The Treasury Bill Theory of Investing Equanimity”: Your ability to stay the course is directly proportional to the amount of short-term safe assets in your portfolio, denominated in years of living expenses. By far the biggest determinant of your investment success is how well you respond to the worst few percent of times, when the world around you and many of the things you had previously taken for granted melt before your eyes. You will experience such moments at least a few times in your investment career, and nothing will see you through them as well as your T-bills and CDs, no matter how low their yield.

Images   When you’ve won the retirement game, stop playing it with the money you need to pay the rent and groceries. I suggest at least 10 years’ worth of basic expenses; 20 years or 25 years is even better. Take whatever risk you like with what assets you have beyond this, whether they’re to buy the odd business-class ticket and the beamer you’ve always wanted, or to bequeath to your heirs, to your charities, and to Uncle Sam, to whom you owe a debt of gratitude for the institutions that made the nation and you along with it wealthy.

Images   Volatility, most commonly measured as standard deviation (SD), is a pretty good measure of an asset’s risk, but it lacks a significant dimension: when its losses occur. A classic example is corporate bonds, particularly lower-rated, high-yield (“junk”) bonds. A given Treasury security and a given corporate security may have the same SD, but the corporate is a whole lot riskier, since in a financial crisis, you’ll be aching for liquidity to purchase stocks at the fire sale or merely to put food on the table. At such times, corporates will get clobbered, while Treasuries will likely rise in price.

Images   The essence of investing is not maximizing returns, but rather maximizing the odds of success, defined as funding retirement, educational expenses, a house down payment, or endowing charities and heirs. Maximizing returns and maximizing the odds of success are two entirely different animals. In other words, more Sylvia Bloom, less Merton and Scholes.

The first stop along that road to maximizing your odds of success is to plumb financial theory for clues on how to do so.

PILLAR ONE

The Theory of Investing

In 1798, a French expedition led by Napoleon invaded Egypt. His forces possessed only the most rudimentary maps and had almost no knowledge of the climate or terrain; unsurprisingly, the invasion was a disaster from start to finish when, three years later, the last French troops, dispirited, diseased, starving, and abandoned by their leader, were mopped up by Turkish and British forces.

Sadly, most investors apply the same degree of planning to their investing, unaware of the nature of the investment terrain and climate. Without an understanding of the relationship between risk and reward, how to estimate returns, the interplay between other investors and themselves, and the mechanics of portfolio design over the approximately half-century of the average investing life cycle, investors are doomed, like Napoleon’s troops, to fail. The book’s first section will deal, chapter by chapter, with each of these essential topics.

CHAPTER 1

NO BALLS, NO BLUE CHIPS

I practiced medicine for most of my adult life, years that confirmed the commonplace belief that physicians are lousy investors.

Two factors make this almost inevitable: first, more than most professionals, physicians suffer from overconfidence; second, they don’t approach finance with nearly the same rigor that they do medicine. Make no mistake about it, finance is as serious a field of study as any physical, biological, or social science, and yet almost no one outside finance—and not just physicians—takes the time to learn its basics.

You expect that your doctor will not treat you for so much as a cold without a thorough understanding of physiology, anatomy, pathology, pharmacology, training in clinical practice, and finally, ongoing surveillance of the peer-reviewed medical literature. Yet most physicians manage their life savings without so much as a glance at the financial equivalents of these areas, the medical equivalent of which would be learning brain surgery by reading the health section in USA Today.

FINANCIAL THEORY: THE RISK PREMIUM

The financial version of physiology—the study of how the body works—is financial theory. If forced to summarize it in a single sentence, it would run: Return and risk are joined at the hip; high returns can only be obtained by taking large risks and sustaining occasional big losses, and safety comes with low returns.

Imagine, for example, that the U.S. Treasury issues a bond yielding 3% in perpetuity—that is, it never matures. Typically, a single bond has a face value of $1,000, so this one yields $30 in interest per year. Now imagine that instead of yielding $30 each and every year, the Treasury secretary flips a coin: heads, that year’s interest is $60; tails, it’s zero.

Over a long enough period, the annual dividend will still average out to $30 per year. Investors, though, displeased by the payout’s unreliability, will price the bond accordingly and reduce it from $1,000 to, say, $750 to compensate for having to bear that uncertainty. At that price, the yield increases from 3% to 4% ($30/$750). In finance-speak, that extra 1% of yield is the “risk premium” for bearing the uncertainty of the coin flip.

“Risk premium” is one of the most important terms in this book. The 1% risk premium in the preceding coin-flip bond example is about what an investor might expect from a bond issued by a company with a low, but not zero, risk of failing.

Stocks carry even more risk than this and thus have a higher risk premium. To bring them into the picture, I’m going to recall from retirement a character from The Intelligent Asset Allocator, your mythical Uncle Fred, who also happens to be your employer.

Soon after signing on with him, he takes you aside and brings you up to speed on the company’s most peculiar retirement plan. At the end of every year, he contributes $5,000 and then offers you this choice:

Option 1: You receive a safe 3% return on the accumulated amount.

Option 2: You flip a coin: heads, your nest egg makes a 30% return for the year; tails, it loses 10%.

You’re going to be working for him for the next 35 years. You know your way around a spreadsheet, and you quickly calculate that with option 1, when you retire you’ll have just $302,310 with which to support your golden years. While this may seem a tidy sum, it’s not; if over the next 35 years inflation runs at its historical 3% rate, you will be left with only $107,436 of current spending power.*

The second choice, with its 50/50 chance of you losing 10% of your nest egg in a given year, breaks you out into a cold sweat. What if you have a string of losing years? If you get tails all 35 years, you could be left with only a pittance for your retirement. On the other hand, if you get heads all 35 years, you know that you will bankrupt poor Uncle Fred with your gains—he will owe you $162,000,000!

Of course, both of these outcomes are vanishingly unlikely: 1/2³⁵, or 0.000000003%, in each case. But it’s still possible to end up behind the first, safe, option, so let’s look a bit more closely at the coin toss. Over a long enough period, you’ll get half heads and half tails. If you represent this with an alternating series of heads and tails, then your return in each two-year period is represented by:

1.3 × 0.9 = 1.17

The first-year return of 30% results in your account being multiplied by 1.3, and the 10% loss the second year, by 0.9. At the end of those two years, you now have $1.17 for every dollar you started with, for an annualized return of 8.17%, which yields an expected risk premium of 5.17% over the safe 3% return of option 1.

You play around a bit more on your spreadsheet and discover that in order to wind up behind the safe 3% option you’d have to get 12 heads and 23 tails or worse. What are the odds of this? You’re not sure, so you visit your former college statistics professor, who treats you to his patented long, sad sigh and points out that you could have easily calculated the odds of any combination of coin flips with something called the binomial distribution function. Your blank look elicits a further sigh; then he heads over to his laptop, fires up a spreadsheet, and after a quick rat-a-tat of keystrokes prints out the graph in Figure 1.1.

FIGURE 1.1 Uncle Fred’s coin-toss probability

You take the graph and spreadsheet file home and figure out that coming out behind the safe option 1 by flipping 12 heads or less has a lower than 5% probability.

I didn’t design Uncle Fred’s coin toss arbitrarily; I chose the +30%/−10% annual outcomes to approximate the annualized return and volatility (risk) of the overall US stock market, and its 5.17% equity risk premium over the safe rate of option 1, which is approximately the risk premium of stocks over T-bills, not only in the United States, but abroad as well. On average you’ll do well indeed by choosing the coin toss, but it comes with breathtaking anxiety each year, and there’s still a small chance that you’ll wish you had taken the safe option.

MATH BOX

Geometric Returns, Arithmetic Returns, and Variance Drag

Some of you may wonder why the return of the coin toss is not 10% instead of 8.17%, since the average of +30% and −10% is +10%. The average return is simply the average of each of the individual annual returns. The annualized return is a more subtle concept. It is the return that you must earn each and every year to equal the median (and most likely) result of your series of differing annual returns.

Imagine that you own a stock that doubles (has a 100% return) the first year and then loses 50% the next year; if the stock was worth $10 per share at the start, it was worth $20 at the end of the first year, and $10 again at the end of the second year. You have earned a zero return, and yet the average return is “25%” (the average of +100% and −50%).

The annualized (geometric) and average (arithmetic) return clearly are not the same—in statistical terms, the latter is the mean, while the former is closer to the median. The coin toss has an average (mean) return of 10% and an annualized (median) return of 8.17%. The annualized return is always less than the average return. If the coin toss comes up with half −10% and half +30% returns, this is the same as having an 8.17% return each year. You pay your bills with annualized return, not average return. The difference between the average and annualized return is roughly half the variance (the square of the standard deviation)—so-called variance drag—the penalty you pay for the high volatility of a security or asset class approximated by:

[Geometric Return] ≅ [Arithmetic Return] – [Variance/2]

If there are no flows into or out of your portfolio, the order of the coin tosses doesn’t matter. But if you are adding or subtracting funds, the order of returns matters a great deal. To take two extreme but highly unlikely outcomes of Uncle Fred’s coin toss, if you add the same amount each year and toss 16 straight heads, then 19 straight tails, you will still end up behind the 3% safe return of option 1; but if you toss 27 straight tails followed by 8 straight heads, you will actually come out ahead of option 1. These are, of course, extremely unlikely events, used only to illustrate that return order does matter, so Figure 1.1, although a simplification, is still a decent representation of the odds in your favor.

Why does the order of the coin tosses matter? Because the 27-tails followed by 8-heads sequence lets the high later returns compound on the largest amount of cash, which overcomes the low early returns. This means that the young person who is actively saving for retirement wants poor portfolio returns up front followed by the high returns later on; a bit later in the book, I’ll explain why the converse, that the retiree wants the good returns up front and the bad ones later, is true and what this means for asset allocation in retirement.

BEYOND THE COIN TOSS

I introduced Uncle Fred’s coin toss as a simple way of illustrating the link between the risk and returns of bonds and stocks; the former is represented by the 3% constant yield of option 1, and the latter by the coin toss, with its 5.17% (8.17% − 3.00%) risk premium. Both were designed to approximate the real world of stocks and T-bills. But where do those returns and risks actually come from? In order to understand this, we need to reverse our perspective from that of the investor to that of someone who needs money to start or grow a business.

Since the dawn of the money economy in the ancient world, there have been only two ways to fund a business: through debt or equity—in today’s world of big business and high finance, bonds and stocks.

Imagine that you’re a budding Middle Eastern–style chef who needs $10,000 to set up a food cart in your neighborhood. Your first choice is to borrow the money from someone. Let’s assume that both you and your friends and relatives don’t have that kind of cash lying around and that you’re forced to go to the bank for a loan.

Let’s further assume that you offer the bank your cart as collateral, that it costs $12,000, and that you have just enough cash to make up the $2,000 difference between the loan amount and purchase price. From the bank’s perspective, the loan is a relatively low-risk proposition: if your business succeeds, it’ll get back the $10,000 loan principal plus interest, and if you fail, it seizes the cart, whose value more than recoups the loan amount. Because of the relatively low risk provided by the collateral backup, the bank charges you a reasonable rate of interest, likely in the vicinity of 6% to 10%. Alas, from your perspective this debt financing is very high risk indeed: if you fail, you’re bankrupt.

The alternate way to fund the food cart is to offer an equity stake to a friend, let’s call her Sue, who has tasted your shawarma and thinks others will find it irresistible. In return for $10,000, you’ll give her half ownership of the business.

The investor/businessperson risk dynamic now flips 180 degrees. From Sue’s perspective, her investment couldn’t be any riskier; if your business fails for any reason—maybe the neighbors don’t like spicy wraps as much as she does, they complain to the zoning board, a pandemic interrupts the supply chain of restaurant supplies and ingredients, or your parole officer finally catches up with you—she loses her entire investment. Finance wonks label Sue the “residual owner” of your food cart; as the cart manager, you don’t have to pay any of the cart’s profits (in the world of stocks, dividends) to yourself and Sue, and if you do, you might want to lower or stop paying out the profits to you and Sue. Her upside is theoretically unlimited; there’s even a tiny chance that in 10 years she’ll be the half owner of an international fast-food conglomerate. Contrariwise, from your perspective, selling her equity (stock) in your food cart lessens your risk, since a failure won’t bankrupt you.

With a bank loan, on the other hand, you’re the one bearing all the risk; if you fail to pay off the principal and interest, you’re legally bankrupt, in which event the bank gets first claim on the cart’s assets.

To summarize: you can fund your business with a loan, which is risky to you and relatively riskless to the lender (think “bond owner”), or you can fund it with equity, which is high risk for the equity owner, but lower risk for you. Since Sue, as a stock owner, is taking a greater risk than the bank, she deserves an equity risk premium. The following table summarizes the risk relationships between the investor and businessperson with debt and equity financing.

One last point: Sue doesn’t need to actually have the money needed to invest in your food cart; she can borrow it. In this case she’s not doing just one risky thing, but two: borrowing money and investing in equity. In the financial world, this is the same as investing in stocks on margin, which, sooner or later, increases the probability of skidding your investment vehicle off the highway of riches and into the ditch.

A perennial personal investment question is whether to use cash to pay off your mortgage or to use the bank’s money to add to your investment portfolio. Putting that money into bonds is often unwise, since your mortgage rate will usually be significantly higher than the bond interest rate. More important, putting mortgage money into stocks is even less wise, since your mortgage effectively becomes a margin loan, albeit one that can’t, like one in a brokerage account, get called and result in your broker involuntarily selling you out of your stocks if their prices fall enough. So pay that mortgage off if you can; the next time the excrement hits the ventilating system, you’ll sleep better.

ANOTHER IMPORTANT TERM: EXPECTED RETURN

“Risk premium” is a relatively easy concept to grasp; not so with a far more slippery one: “expected return.”

God only knows if your shawarma stall succeeds. Assume that there’s a 40% chance that over the next 10 years it does well and that you spend all its profits to turn it into a fashionable restaurant that can be sold for $200,000. In that event, Sue gets half—$100,000. Further assume that leaves a 60% chance that it goes kerplunk; if we weight each of Sue’s two possible outcomes, either $100,000 or zero, by their probabilities, we see that Sue’s expected payoff is $40,000 (0.4 × $100,000 plus 0.6 × $0).

The expected quadrupling of Sue’s money over 10 years calculates out to an expected return of 14.9% per year.* That high expected return sure sounds juicy, but a high expected return always comes with a tank car full of risk, in this case, the 60% chance that Sue loses every last penny; this additional risk is the reason why stocks offer higher expected returns than safe assets: the “equity risk premium.”

HOW DO WE ESTIMATE THE EXPECTED RETURN OF STOCKS?

In the real world, companies resemble living organisms: they are born, they may or may not grow, and then they die. Most animals live only a very short period of time, while some, like the Greenland shark, may live three centuries, and some invertebrate species and trees, like the bristlecone pine, survive for millennia.

In the same way, only about half of small businesses survive 5 years, and the half-life of publicly traded companies is about 10 years. Some small privately owned American businesses have operated since before the Revolutionary War, and a few, like the two large corporations launched by J.P. Morgan—General Electric and U.S. Steel—have traded on stock exchanges for more than a century.

Since most companies disappear, nearly all they leave their investors with is the dividends they (or the companies that take them over or merge with them) pay out before they die; this is the only proper way to value a stock. At present, for example, Facebook/Meta Platforms does not pay a dividend; if it manages to go bankrupt or get shut down by the government before it does, it will hand its final investors a total loss. (An exception to “all companies die and leave nothing but their dividends” occurs with a cash buyout, which accounts for only a tiny amount of overall equity market return.)

The easiest way to understand the expected return of equities is to imagine a mythical stock market that always yields an aggregate 3% dividend and whose dividends grow at a constant rate of 5% per year. Let’s start with a stock index share price of $100 and a dividend of $3; next year, the dividend will have grown by 5% to $3.15, so the index price should also increase by 5% to $105 to keep the yield constant at 3% ($3.15/$105.00 = 3%). Theoretically, each year you’re getting a 3% dividend and 5% of price increase: 8% (assuming the dividend is not reinvested). This simple arithmetic relationship,

Expected Return = Dividend Yield + Dividend Growth

is called the Gordon equation; it should be front of mind for any long-term investor.

SEX, LIES, AND THE DISCOUNT RATE

Let’s return to the two mythical Treasury bonds that never matured at the beginning of the chapter, the ones with perpetual $30-per-year interest payments, the first paying a regular $30 in annual interest, and the second paying a coin-flip-determined $60 or $0.

Recall also that we started with the first bond’s price of $1,000 and a 3% yield, thus the $30 annual interest. But there’s a better way of looking at this mythical bond, which is to reverse the process and ask what discount rate we apply to that $30 per year interest to get its market price. If we apply a 3% discount rate to it, we get $30/3% = $1,000. And because the second bond with the coin-flip interest payment is riskier, we applied a higher discount rate to it: 4%. This values the income stream at $30/4% = $750.

This gets to the central truth of investing: the real value of your assets is not the number on your brokerage statement, but the stream of income it provides: in the case of a bond, the interest payments, and with stocks, the dividend payments, or perhaps more romantically, your own little slice of the economy.

The British have a several-century head start over us Yanks in this department. Until recently, had you asked someone from the United Kingdom about somebody’s net worth, the most likely response would have been along the lines of “She’s worth about 20,000 a year.” Americans, in contrast, fall in love with the numbers on their brokerage statements, the problem being that, as you can see from the previous calculation, those are exquisitely sensitive to the discount rate denominator, which rises and falls with the market perception of risk. For example, during the global financial crisis, the financial markets decided to increase the discount rate dramatically, which had the inverse effect on prices.

The reverse occurs during stock manias, when the market decides to apply a much lower discount rate. Perhaps the most spectacular example of this phenomenon was James Glassman and Kevin Hassett’s Dow 36,000. At the time of the book’s 1999 publication, the market seemed to apply roughly a 9% discount rate to the stock market’s future earnings, as reflected in the Dow’s level of about 10,000 at the time.

Nonsense, said the authors, investors would soon come to understand that stocks were not at all risky in the long term and thus apply a far lower 3% discount rate to its future dividends, which would triple the price within a few years.¹ Needless to say, that didn’t happen. The Dow did temporarily reach 36,000—22 years later and not before twice falling by about half along the way. Based on the historical market share price increase of 6% per year, I fearlessly predict Dow 100,000 in 2040.

MATH BOX

The Gordon Equation, Risk, and the Discount Rate

The previous narrative explanation of the Gordon equation hides the more complex math behind it, central to which is the discount rate. Let’s say someone offers you the choice of a cheeseburger for lunch today or more than one cheeseburger in 10 years. How many would make it worth the wait? Say you want two; your discount rate for cheeseburgers is thus 20.1 – 1 = 7.2%, which is the rate of compound interest needed to double your burgers in 10 years. (This is an easily understood example of the Rule of 72: the interest rate times the doubling time approximates to 72 [7.2 × 10]; the doubling time at an interest rate of 12% is 6 years. Human beings are terrible at calculating exponential growth, and the Rule of 72 is a good way of handling that deficiency. Let’s say that you’re out for a walk without a calculator in your pocket, and it pops into your head to estimate how much a dollar grows over 50 years at a 10% return rate. That means it doubles about once every 7 years; over 50 years, it’ll double about seven times, or to $128—as in $2, $4, $8, $16, $32, $64, $128—which gets you into the ballpark of the actual answer, $117.39.)

Now, let’s say that the person offering you the deal is very old or personally unreliable and might not show up to make good on the cheeseburgers. In that case, to compensate for the risk that you might not get them, you’re going to want more cheeseburgers—say 5, in which case your cheeseburger discount rate is now much higher: 50.1 – 1 = 17.5%.

The discount rate is thus the return you demand to compensate for the risk of owning an asset and is a good way of understanding the close connection between risk and return.

Suppose a company yields a stream of dividends that grows at a rate of g that extends indefinitely into the future, and that those dividends are discounted by the expected return, r; in that case, today’s price for the company, P₀, is this infinite sum of all the future dividends:

Financial economists refer to this formulation as the “dividend discount model.” Note that the dividend growth rate g cannot be greater than the discount rate r, since that would make the company’s value today infinite.

If we apply a bit of calculus to the preceding formulation and solve for r, the discount rate/expected rate of return, we get

R = D₁ + g

This simple equation is nearly identical to the simplified equation we derived in narrative fashion earlier, save for the fact that D₁ is the dividend next year divided by today’s price. D₁ takes the place of today’s dividend yield, D₀, in the simplified equation—close enough for our purposes.

FROM EXPECTED RETURNS TO REALIZED RETURNS, OR THE IMPORTANCE OF GETTING “REAL” ABOUT INFLATION

Those of you with sharp eyes will have noticed that, although I just told you all companies eventually die, I still assume that the overall market’s earnings and dividends continue indefinitely into the future. This is because it’s far less likely that a nation’s entire stock market will die. This occasionally happens, but when it does, you’ve got far bigger problems than your retirement portfolio.

How well does the Gordon equation work in predicting the return of the overall stock market? Currently about 3,500 US companies trade on the stock exchanges, and very high-quality data on their returns are available from 1926. Let’s pretend that you were an investor in that year who wanted to estimate long-term future returns. How would you do it?

Let’s put ourselves in the place of that investor on January 1, 1926. Stocks yielded about 5.0%, and dividends had been growing at about 1.6% per year over the past half-century. The reasonable investor would have predicted a return of 5.0% + 1.6% = 6.6% going forward.

While today’s investor would immediately worry about how inflation would have eroded this return, that wasn’t much of a concern in 1926, since during the previous half-century prior to that year, there had been only about 0.7% of annualized inflation. This 0.7% inflation lowered the inflation-adjusted expected return to 5.9%. In fact, between 1926 and year-end 2021, the S&P 500 returned 7.35% after inflation, 1.45% higher than predicted by the Gordon equation.

From this point on in the book, we’re going to be talking about your future personal consumption of goods and services, wealth, and investment returns mainly in inflation-adjusted, or “real,” terms, so keep a sharp eye out for the word “real.” This takes a little getting used to. For example, over the past century U.S. Treasury bills, which most finance practitioners consider the preferred safe asset, have returned 3.26% per year, versus inflation of 2.90%, thus yielding only a tiny sliver of real return. In other words, a dollar invested in T-bills has, on average, slightly outpaced the prices of the stuff you want to buy.

Why the 1.45% gap between the 5.9% expected real return calculated in 1926 and the 7.35% real return realized in the 96 years that followed? That’s because during those 96 years the dividend yield fell from 5.0% to 1.26%. In other words, in 1926 getting a dollar of dividends required purchasing only $20 of stocks. By the early twenty-first century, stocks have gotten a lot more expensive. At the end of 2021, you had to purchase nearly $80 of stocks to get that same dollar of dividends. Thus, the “dividend multiple” almost quadrupled, which, over the 96 years between 1929 and 2021, which annualizes out to an increase of 1.45% per year—precisely explaining the gap.

So let’s add another term to the Gordon equation so that it yields the realized return, the return you actually got:

Realized Return = Dividend Yield + Dividend Growth + Annualized Change in Dividend Multiple

The first two terms in the preceding equation, the dividend yield plus the dividend growth, “the expected return,” has also been called the “fundamental return” of the market—what you’ll get if the dividend multiple doesn’t change. The preceding equation simplifies to:

Realized Return = Expected (Fundamental) Return + Annualized Change in Dividend Multiple

The expected (fundamental) return is an easily calculated number and, more important, a more stable one. On the other hand, the annualized change in multiple, as we’ll soon see, fluctuates, sometimes wildly, and is completely unforecastable and thus unknown—better to call it the “speculative return.” We can summarize all of this colloquially as:

Actual Return = Fundamental Return + Speculative Return

On any given day, or even in any given year, the speculative return (the change in multiple) overwhelms the fundamental return. For example, in 2008 the dividend multiple, and the speculative return along with it, fell by 42%, and in 1933, they rose by an astonishing 66%, while in both years, the fundamental return changed by only a few percent.

Even over 10-year periods, real annualized returns can deviate wildly from the Gordon equation estimate, derived from the starting S&P dividend yield and the 1.46% long-term real dividend growth rate of the twentieth century, as demonstrated in Figure 1.2.

FIGURE 1.2 Ten-year inflation-adjusted S&P 500 returns predicted by Gordon equation versus actual returns

Only over very long periods, on the order of a generation, does the Gordon equation provide a reasonably accurate estimate of future returns, as seen in Figure 1.3.

FIGURE 1.3 Thirty-year inflation-adjusted S&P 500 returns predicted by Gordon equation versus actual returns

Figure 1.4 illustrates, in simplified fashion, the relative importance of the fundamental and speculative returns.

FIGURE 1.4 Signal versus noise: fundamental (expected) versus speculative (multiple change) returns over time

Even over the nearly one century between the year ends of 1925 and 2021—longer even than Ms. Bloom’s investment horizon—the spectacular fourfold increase in the dividend multiple still accounted for a fifth of the total real stock return (1.45% of 7.35%).

What does this tell us about expected inflation-adjusted returns going forward? Start with the 1.7% dividend yield at the end of 2022. Real dividend growth since 1926 was about 2.0% per year. If the multiple doesn’t change, we can expect a real return of 1.7% + 2.0% = 3.7% from stocks.*

But even over very long time periods, realized total returns can vary widely. For example, at the end of 2022, the 30-year annualized real return of the S&P 500 was 7.0%, while the forecast per the Gordon equation from 30 years before, at the end of 1992, was 4.8%. That doesn’t sound like a very big difference, but compounded over 30 years, that 2.2% gap results in a nearly twofold difference in end wealth.

At best, the Gordon equation gets one into the ballpark over very long periods, but because of the “magic” of compounding, being off by even a few percent of annualized return can lead to large differences in the end wealth actually achieved over the several decades of one’s investment career.

WHAT DO THE DATA ON INTERNATIONAL STOCKS TELL US?

Clearly, American shareholders have done very well indeed over the past century. Given that at least some of that salutary experience has been due to the increasing valuations applied to earnings and dividends, it makes sense to look also at security returns abroad.

While equity returns in the United States have been above the global norm, they haven’t been exceptional. Around the world, it seems, stocks have also behaved the way they’re supposed to, offering returns that are uniformly higher than those offered by bonds and bills. In 2002, academics Elroy Dimson, Paul Marsh, and Mike Staunton (DMS) celebrated this fact in their aptly named Triumph of the Optimists, and each year thereafter they’ve confirmed the good news in their annual research reports sponsored by Credit Suisse, the summaries of which are freely downloadable.²

Figure 1.5 summarizes their results for the 122 years between 1900 and 2021 for the returns of stocks and short-term government bills. In each nation, stocks return more than bonds and bills, and in every case but one, bonds have higher returns than bills, just as we would predict from theory.

FIGURE 1.5 Major-nation inflation-adjusted annualized returns of stocks, bonds, and bills, 1900–2021

Source data: Credit Suisse Global Investment Returns Yearbook 2022.

While the “efficient market hypothesis” (EMH, which we’ll discuss in much greater detail in Chapter 3) predicts that stocks’ risk-adjusted expected return should be the same in all countries, notice how all of the world’s English-speaking nations sit on the top half of the graph—only Finland, Denmark, and Sweden have higher returns than the lowest-returning English-speaking nation, the United Kingdom.

Is there something about the English language that produces healthier economies and higher security returns? While a Marxist might opine that this is due to England’s long history of colonialism and slavery, this hypothesis does not fit the data. Portugal, Spain, and France were no slouches in those departments: Portugal had the highest ratio of slave holdings to population of any nation in history, yet it wound up poorer and with lower investment returns than its northern cousins. Were colonialism really a factor, then Hong Kong and Singapore, which were colonies until very recently, would be among the world’s poorest nations, and Ethiopia, which except for a few years in the 1930s has been independent for millennia, should be among the wealthiest.

It’s not the English language, but rather English common law that produces these high returns. The secure ownership of both stocks and bonds depends on the common-law institutions that protect property rights. For this reason, while I think that emerging markets stocks have a place in the well-diversified portfolio, I’m not overly optimistic about them, since many nations in that group have less than stellar legal systems. The poster child for this problem is China, which despite blistering economic growth has had miserable stock returns—a nominal 1.2% between 1993 and 2021, which is slightly negative in real terms.

DO STOCKS GET LESS RISKY OVER TIME?

A quick glance back at Figure 1.3 might suggest that stocks get less risky over time. After all, the lowest 30-year annualized real return was 4.14%, which grew an inflation-adjusted $1.00 into an inflation-adjusted $3.36. The maximum 30-year annualized real return was 11.80%, which grew a real $1.00 into $28.37, enough to provide all but the most dilatory savers with a generous retirement. While the lowest 30-year real return of 4.14% doesn’t look all that awful, it was far more likely to leave the impecunious retiree with parlous finances.

As we’ll find out in Chapter 3, stocks approximately follow what’s known as a “random walk,” which means that the longer the period studied, the wider the dispersion of final dollar values for different stocks or stock portfolios. Put options, which give their buyers the ability to sell stocks or market indices at a given price, provide a useful tool to study this issue. These instruments function as insurance against market declines, and their issuers—the individuals and institutions who “write” them—must be compensated handsomely for providing protection against losses in stock values. Were stocks less risky over longer periods, their cost would decrease the longer their duration. In a famous 1995 paper, academic Zvi Bodie demonstrated exactly the opposite: over increasing time horizons, put options become more expensive.³

On the other hand, the work of DMS on international stock returns shows that in all 21 nations studied, stocks had a positive return over the 122 years prior to 2022, and in every single nation they returned significantly more than bonds and bills. Note, however, this list of 21 nations benefited from “survivorship bias,” since not all financial markets in existence in 1900 survived over the next 122 years. More than a few countries in the DMS database did not, suffering such “discontinuities” as the long-lasting closure of the Saint Petersburg bourse in 1917 and the Shanghai Stock Exchange in 1950. This survivorship bias implies that the returns displayed in Figure 1.5 may overestimate both future stock and bond returns. Still, the fact remains: over the longest time periods, the equity risk premium—the extra returns offered by stocks over those offered by bonds and bills—remains positive.

In reality, the “less risky/more risky with time” question is meaningless without first answering the question: for whom? The period between 1967 and 1996 provides a good laboratory in which to examine this question.

Over those 30 years, the CRSP US total stock market index returned an annual 6.09% after inflation, near its historical average. But, oh, how it got those returns: a real 0.40% per year during the first 15 years, which saw severe inflation that was cured by a Paul Volcker–led Fed tightening of the money supply and a fearsome recession that destroyed Gerald Ford’s reelection prospects and roiled the stock market. As inflation receded and the economy came roaring back, the second 15 years featured a real 12.10% return.

To understand how the risk of a poorly performing stock market plays out within an investment portfolio, I’m going to introduce two different individuals whose working and saving careers encompassed that 30-year period between 1967 and 1996. The first person, whom we’ll call Mr. Forward, invested $100 per month in 1967 dollars in the US total stock market, as represented by the CRSP 1–10 index, an excellent proxy for the total US stock market. Thus Mr. Forward made a total of 360 contributions, starting with $100 on January 1, 1967, then increasing each month with inflation. The second person, Mr. Reverse, did the same thing, except that he experienced the monthly returns in reverse sequence. That is, he got the December 1996 returns first and the January 1967 returns last.

Figure 1.6 shows what happened, which was a classic tortoise-and-hare race. Mr. Reverse, who got the high returns first, initially took the lead, but Mr. Forward, who got the high returns last, handily won, with an end wealth of $149,436, compared to Mr. Reverse’s $69,291 (in January 1967 dollars, or roughly $775,000 and $361,000, respectively, in January 2023 dollars). The reason for Mr. Forward’s victory? His high-return years compounded over the far larger pile of assets during the second half of the period, as opposed to the small amount of assets in Mr. Reverse’s high-return years during the first half.

FIGURE 1.6 Results of investing $100 in inflation-adjusted dollars per month, 1967–1996 (see text)

Were the industrial-grade volatility and poor returns of the first half of the period (1967–1991) risky for the saver? Quite the opposite; even Mr. Reverse’s poor showing nearly doubled his total real investment of $36,000. Young, periodic savers should get down on their knees and pray for a severe bear market at the beginning of their investment journeys, so as to acquire shares on the cheap—that is, assuming they can find a job well paid enough to allow savings during the attendant hard times.

Now let’s run the same sort of experiment at the opposite end of life with two retirees who invest a nest egg of $100,000 in 1967 in the US total stock market, and who spend $5,000 per year in real 1967 dollars each year—that is, a 5% inflation-adjusted “burn rate.” Figure 1.7 tells the sad tale of Mr. Forward, who lived those years in the stock market as they actually occurred.

FIGURE 1.7 Retirees with a 5% real burn rate, 1967–1996 (see text)

Mr. Forward watched in horror as the 1967–1981 bear market chewed away his portfolio in fits and starts. The great bull market that began in 1982 arrived too late for him; in the middle of year 26, he ran completely out of money. Meanwhile, Mr. Reverse, who got the returns sequence in reverse, left happy heirs. His nest egg was inflated by the initial boffo returns to the point that his starting $100,000 wound up worth $301,000 in 1967 dollars—$1.57 million in 2023 dollars—when he shuffled off his mortal coil after 30 happy years of retirement.

The conclusion: for the retiree who receives a bad initial-returns draw, stocks are risky indeed, a phenomenon known as “sequence-of-returns risk.” Contrariwise, for the young saver, as long as he keeps his cool during the discouragement that attends the inevitable bear markets that all long-term investors will encounter, stock market risk is a snooze.

THE EXPECTED RETURN OF BONDS

Estimating the expected return of a bond—a security that pays regular interest, then returns the purchase face value to the investor—seems easy at first: if you buy a 30-year Treasury bond with a yield of 4.00%, that’s pretty much what you’ll get. (It won’t be exactly 4.00%, since you’ll be reinvesting the interest at different rates along the way.)

So far, so good. The trouble is that 4.00% return is “nominal,” that is, in current dollars, and because of inflation, it buys less with each passing year. How much less? Fortunately, the Treasury also issues inflation-adjusted bonds (Treasury Inflation-Protected Securities, or TIPS), whose principal and interest keep pace with the Consumer Price Index (CPI). As of this writing, they yield about 1.5%, but as recently as 2021, their yields were persistently negative, as low as −1.9% for the 5-year security. You’re reading that right. In 2021, our after-inflation interest and principal value lost 1.9% of its purchasing power for five full years. (By the way, despite apparently high current inflation as of this writing, the difference between the rates of ordinary bonds and TIPS of 30 years maturity—the so-called break-even yield—is telling us that the bond market thinks that over the next 30 years inflation will run 2.3%.)

Can you do better than Treasuries, either TIPS or the “plain vanilla” nominal bonds? Corporate bonds throw off higher interest, and you can dial in as much of them as you want, coupled, of course, with an appropriate amount of risk.

Companies can default and do go bankrupt, but bondholders sometimes eventually recover some of their assets in bankruptcy proceedings, on average about half of the defaulted interest and principal. The most important metric of a portfolio of corporate bonds is the “loss rate”: the total net return lost each year to bankruptcy after recovery in court. The loss rate for Baa bonds—the lowest “investment grade”—averages around 0.2% per year. Considering that Baa bonds are currently yielding 2% more than safe Treasuries, they seem, at first blush, like a bargain.

The problem is that on its way to default and loss, a bond will get sequentially downgraded; so while it’s rare for a highly rated bond to drop off a cliff into default, it’s far more common for it to be downgraded step by painful step before it finally defaults, as happened to the most notorious corporate bankruptcy of this century, Enron. Even bonds with Aaa ratings—Moody’s highest—have suffered a downgrade rate of about 10% per year. The longest series of corporate bond returns show that, averaged over all grades, they yield about 1.6% more than Treasuries of the same maturity, about half of which is lost to bankruptcy, thus offering about 0.8% of extra return.⁴

Is this 0.8% extra return worth the risk? No. The loss rate of corporate bonds is lumpy—normally low, but high during times of economic turbulence. Figure 1.8 plots the loss rate for all corporate bonds between 1983 and 2020.

FIGURE 1.8 Loss rates for all corporate bonds, 1983–2020

Source data: Moody’s Annual Default Study

The graph in Figure 1.8 gets to the essential nature of risk: bad returns in bad times, a phenomenon I’ll refer to going forward as “Ilmanen risk,” after colleague Antti Ilmanen, who wrote extensively about the importance of timing.⁵ Notice how corporate bonds experienced losses at the worst possible times: during the savings and loan failures around 1990, the tech bust of the early 2000s, the global financial crisis of 2007–2009, and in 2020 during the economic turbulence at the pandemic’s onset. In other words, corporate bond losses hit the hardest when you’re most likely to need cash to purchase stocks when they’re cheap, to snap up the coveted corner lot of your overextended neighbor, or merely to pay for groceries and rent after you’ve been downsized. Buying stocks in the teeth of a bear market never feels good; it feels even worse when the bonds you’re selling to do so have hit the discount rack.

In contrast to corporate bonds, a small corner of the fixed-income market deals with so-called catastrophe bonds, whose principal is wiped out by a “trigger event,” typically a hurricane or earthquake. Since hurricanes and earthquakes are uncorrelated with financial crises, they offer lower expected returns than similarly rated corporate bonds. This evokes a principle that bears repeating: risk is not just about how much you lose, but also when you lose it.

This is true of other assets as well, the classic example being gold, which often does well when stocks and bonds tank; thus, its expected return should be low, which is well reflected in its realized return. Over the past two millennia, the yellow metal’s real return seems to be zero: in ancient Rome an ounce of it bought a fine toga, and today it buys a good-quality men’s suit.

High-quality corporate bonds can be thought of as perhaps a 90/10 mix of Treasury bonds and stocks, and high-yield (“junk”) bonds as something close to 50/50. As discussed in the Introduction, to mitigate the biggest risk to your portfolio—your mental health, and hence your investment discipline—during the worst of times, it’s best to keep your stocks and bonds in entirely separate mental accounts and to own only the safest fixed-income assets.

HOW EXPECTED RETURNS LOOK IN 2023

This is my fourth book for individual investors, published, respectively, in 2000, 2002, 2009, and 2023. Here’s what expected real returns for stocks and bonds looked like in each of those years as calculated in this chapter, the calculated expected return of a 60/40 portfolio, and the realized real returns of the 60/40 portfolio from book publication to the end of 2022:

*Realized real return for 60/40 mix of S&P 500 and Bloomberg Aggregate Bond Index, rebalanced annually, from end of book year publication.

With all three prior books, these estimates turned out to be pessimistic; that is, in each case, the realized return was higher than the expected return I calculated. Note, however, that the older the book and the longer the forecast period, the lower the gap. I published The Investor’s Manifesto a scant 12 years ago in the teeth of the financial crisis, and it seems almost ludicrous to extrapolate the 5.5% real return for a 60/40 portfolio obtained since then into the future.

In each case, a 60/40 portfolio did better than forecast for a single major reason: falling interest rates drove up the returns of both stocks and bonds, a factor that seems unlikely to persist.

Finally, the sharp-eyed reader will notice that even the lowest 30-year annualized real stock return from Figure 1.3 of 4.14% is still higher than my current estimated future real return of 3.7%. In the words of Dimson, Marsh, and Staunton (DMS), over the past century the optimists have indeed triumphed, in no small part because of the near quadrupling of the dividend multiple over that period. Unless this process continues, the high historical stock returns will recede into the rearview mirror. If the process continues to reverse as it did in 2022, there will be no small amount of pain.

This analysis agrees with the estimated stock returns predicted by the DMS data, which show that the average equity risk premium—the difference between stock and bill returns—over the 122 years for the aggregate world stock market was 5.0%. However, 0.7% of that came from expansion of the dividend multiple, for an expected equity risk premium of 4.3%.⁶

***

Since the dawn of recorded history, investors could either lend or own a piece of a business: debt or equity. The last major change to that occurred four centuries ago, when it became possible to buy and sell that debt and equity on the open market. That’s about it—debt and equity, end of story.

Is there anything else? What about commodities like oil, timber, or wheat? Unless you want to install a large tank, lumber yard, or grain silo in your backyard, you’re limited to futures contracts, a zero-sum game with significant investment expenses and an enormous short-term emotional toll. Further, the increasing popularity of commodities futures investing has pushed up the prices of futures contracts, which results in a phenomenon called contango. This is not a dance done in Buenos Aires, but rather a process that, on average, subtracts several percent of return annually from commodities futures returns as the higher-priced contracts for future prices slowly roll toward the lower spot price—the price at which the commodity is selling today (which you can’t access, as noted, without a backyard petroleum tank).⁷ Unlike crude oil or soybeans, you can store a reasonable amount of gold, but as we just saw, it has about zero long-term real return. The same is true of silver, which over the past few centuries has also barely held its purchasing power.

What about real estate? In general, it holds its real value and yields rental income, but owning property isn’t so much an investment as it is a job. If you like fixing toilets and dealing with drug-addled, gun-toting deadbeat tenants, be my guest. True, you can pay a management company to do that for you, but this service doesn’t come for free, and even in the best of circumstances you’re limited to an undiversified mix of relatively few properties. This limitation can be avoided by owning a portfolio of real estate investment trusts (REITs), but by the time you’ve arrived at that high level of diversification and size, you now simply own . . . equity shares. Private real estate funds and syndications lie midway between individually owned property and REITs, but are still highly illiquid and insufficiently diversified.

I’ve spoken to more than a few enthusiastic commercial property and apartment owners lately. Nearly all of them seem to have either forgotten or are too young to remember how rents fell and tenants let leases lapse following the 2007–2009 financial crisis.

Finally, what about cryptocurrency? If you believe its enthusiasts, it’s money freed from the specter of the government’s prying eyes and printing presses. You can even earn interest on it, as long as you’re willing to take in yet more cryptocurrency and don’t mind taking the risk that the founder of the “bank” paying you that interest might turn out to be a blatant fraudster, instead of the altruistic visionary portrayed in his or her initial press coverage. If I want to own currency, I’ll take it in dollars, euros, yen, and pounds sterling, thank you. Crypto technology may well revolutionize finance—so did the appearance of stamped metal coins millennia ago and paper money after that—but over the centuries since these marvellous inventions, holding them in your safe or purse hasn’t proved a paying proposition.

CHAPTER 1 SUMMARY

Images   There are only two forms of participation in the financial economy: loaning money at interest (debt) or sharing ownership (equity). A company’s residual owners, its shareholders, get paid last and are in a far more tenuous position than debt holders. They frequently suffer share price declines, and they thus demand a higher expected return to compensate for that risk.

Images   A debt or equity’s expected return is a probabilistic estimate that averages together in weighted fashion all the possible return outcomes. The simplest example of this is this chapter’s food cart, with its 40%/60% probabilities of $100,000/$0 payoffs, yielding an expected payoff of $40,000. The realized return is what you get after the dust settles, which can be far higher or lower than the expected return.

Images   The fundamental expected return of a stock or stock market is the sum of its dividend yield and expected dividend growth.

Images   The realized return of a stock or stock market is equal to the fundamental return plus the speculative return, the change in the dividend rate. The speculative return can swing wildly, and over periods of up to a generation it often overwhelms the fundamental return.

Images   In the worst of times, the prices of both debt and equities can fall dramatically. To compensate their owners for the high perceived risk at such times, their expected returns must rise dramatically. Most of the time, purchases made at such times do well. Unless they don’t.

Images   The past four decades in the capital markets have been one long beer and pizza party. The year 2022 saw some dieting; both financial history and simple prudence suggest the possibility of more of the same.

Images   Investing demands diligence and hard work, and occasionally you will suffer substantial losses. The odds are in your favor if you can stay the course through the worst of times. Maximize your odds of doing so with a nice pile of “sleeping money”: short-duration Treasury securities and FDIC-guaranteed certificates of deposit.

* The sharp-eyed may notice that $107,436 is a good deal less than 35 × $5,000 = $175,000; for simplicity, I have not increased the annual contribution by the 3% historical US long-term inflation rate, as it does not materially affect the point of the exercise.

* This is the annual rate of return needed to turn $10,000 into $40,000 over 10 years (40.1 – 1 = 14.9%).

* Some have suggested that stock buybacks have added a “buyback yield.” This is a dubious proposition; buybacks reduce both dividend payouts and critical reinvestment in business. Most buybacks generally provide shares for executive option compensation, are a form of executive salary, and do not result in increased shareholder ownership of the firm. Moreover, most buybacks occur when corporations are flush with cash at high equity prices and are thus poorly timed.

CHAPTER 2

ODDS AND ENDS

DO SOME STOCKS HAVE HIGHER EXPECTED RETURNS THAN OTHERS?

Let’s return to the hypothetical example of our coin-flip Treasury bond, whose random payoff mandates a 1% “risk premium” over the return of a conventional Treasury bond. The same thing is true for stocks. Imagine that Company A and Company B have the same average level of earnings and earnings growth, but Company A’s earnings and growth are steady and regular, and Company B’s bounce around from year to year.

In this case, the stock of steadier Company A will command a higher price and have a lower return than the stock of Company B. All else being equal, companies that sell necessary staples that consumers need even when the economy’s tanked—food, medicines, bathroom tissue—will sell at higher prices than companies that make new automobiles and luxuries, and whose purchases can be deferred.

Human behavioral biases can also bid up the price of a stock and thus lower its expected future returns. For example, investors prefer glamorous firms with charismatic leaders in rapidly growing fields over dowdy companies in smokestack industries. Sexy companies command higher prices for every dollar of their earnings, and their perceived strength lowers the return that investors demand for owning them. Think about it: Amazon and Caterpillar walk in the room and ask you for capital. You’re going to demand a much higher return from Caterpillar than from Amazon. (In this context, the verb “demand” is a financial term of art that refers to the expected return that an investment must offer to attract buyers.)

Is this really true? Do “bad companies” have higher returns than “good companies”? It turns out that over very long periods they seem to, for at least three reasons. First, as we’ve seen, they’re riskier. Their cash flows tend to be less steady, and they also tend to be more heavily indebted and thus do especially poorly during economic crises, as occurred during the Great Depression and the more recent global financial crisis, as shown in the following table.

Source data: Kenneth French Data Library

The numbers for the 1929–1932 bear market are especially frightening. For each dollar of large growth stocks held at the top, the investor was left with 18 cents at the bottom; for each dollar of large value stocks, 12 cents; and for the more recent financial crisis, a dollar of growth stocks fell to 55 cents, whereas a dollar of value stocks fell to 37 cents. So indeed, value stocks have historically had higher returns than growth stocks, but that extra return came at the price of higher risk.

Admittedly, there are counterexamples to the preceding risk-based explanation, particularly the salutary performance of the value factor during the tech bust of 2000–2002. This suggests a second reason for the value premium: investors systematically overestimate the growth potential of glamorous companies. In a 1993 landmark study, Russell Fuller, Lex Huberts, and Michael Levinson looked at multiple portfolios, among which were glamorous growth stocks, defined as the top fifth of the market in terms of their price-to-earnings (P/E) ratio; values stocks, in the bottom fifth of P/E; and the overall market.

The growth stocks initially sold for a P/E of 25.6, which meant that for every $1,000 worth of shares, they earned $39 in profits. The “market” stocks sold for a P/E of 9.8, earning $102 per $1,000 held. The value stocks sold for a P/E of 6.8, earning $147. (If these earning yields seem high by current standards, they are. The study period, from 1973 to 1990, saw equities selling at far cheaper prices than they do today.)

Right off the bat, the value stocks produced almost four times as much earnings per dollar invested than did growth stocks. Did the growth stocks’ earnings ever catch up? Not even close. Figure 2.1 plots out what happened to the dollar earnings of the three groups over the next 8 years. The growth companies did indeed increase their earnings faster than the overall stock market, just not for very long or by very much. They grew their earnings about 10% faster than the market in year one, 3% faster in year two, 2% faster in years three and four, and only about 1% faster in the four years after that, an advantage so small that you can barely see it in the plot. Concurrently, the value stocks—the ones with the lowest P/Es—grew their earnings 10% slower than the market in year one, but that deficit improved rapidly, and their earnings growth matched the market’s by year six.¹

FIGURE 2.1 Earnings per $1,000 of stock value for growth stocks, value stocks, and the overall market

Source data: Fuller et al.

By the end of the eighth year, the growth stocks’ earnings remained well below that of the value stocks. Even worse, after eight years, the earnings growth rates for the original growth and value cohorts had equalized.

The third reason why value stocks have historically outperformed growth stocks is the asymmetric way that the markets react to earnings surprises in the two groups. Eventually, market participants notice that a growth company’s earnings are not living up to expectations and punish its shares. Researchers David Dreman and Michael Berry observed the price movement of growth company stocks with earnings announcements. When earnings exceeded expectations, they beat the market by 6.63% over the following quarter, but when they had disappointed expectations, they lagged the market by 18.49%—three times as much. In early 2022, Facebook (recently renamed Meta Platforms) offered up a stunning example of this phenomenon when its shares skidded 26.4% in a single day when the company missed analyst estimates of revenue and earnings.

Contrariwise, Dreman and Berry observed that when value stocks exceeded expectations, they beat the market by 20.05%, but when they underperformed expectations, they lagged the market only 4.19%—one-fifth as much. To summarize: When a growth stock exceeds expectations, it does just OK, but when it fails them, look out below. But when a value company beats expectations, it does very well indeed, and even when it disappoints, it isn’t hurt too badly.²

In a massive study, Eugene Fama and his coauthor Kenneth French found the same thing with firm profitability. Although growth stocks were initially far more profitable than value stocks, growth stocks’ profitability gradually deteriorated, whereas that of the value stocks gradually improved. All else being equal, that should translate into better price gains for value stocks.

The shares of small companies may also have higher returns than the market, for the simple reason that they are riskier. In 1981, academic Rolf Banz reported that small-cap US stocks had higher returns than large ones.³ In 1992, in a landmark article in Journal of Finance, Fama and French confirmed this. They also noted that both small-cap value stocks and large-cap value stocks indeed had higher returns than the market. Further, they discovered that the behavior of any given portfolio could be well explained by the influence of three factors:

1.   The market factor: the return of the total stock market (represented by CRSP 1–10 Index) minus the T-bill return

2.   The small stock factor: the return of the small company stocks (the sixth through tenth deciles of the CRSP Index) minus that of large company stocks (the first through fifth deciles)

3.   The value stock factor: the returns of the cheapest 30% of stocks minus that of the most expensive 30%

Between mid-1926 and the end of 2021, the returns and standard deviations (SDs) of all three factors are shown in the following table:

Source data: Kenneth French Data Library

To reiterate, the overall market factor is the market return in excess of the T-bill rate, the small-company factor is the return of small companies minus that of large companies, and the value company factor is the return of value companies minus that of growth companies. Note that the small and value factors are long/short portfolios, so even in the best-case scenario, the investor who is not shorting large or growth company stocks will get only about half of these factor returns.

Note also that the small company factor is not particularly impressive: its SD is six times bigger than its return, which means that in any given year it’s not much better than a coin flip. The value factor is only slightly more impressive in that regard. To reiterate, the small and value factors are long/short portfolios, so unless you’re willing to short a huge number of stocks, you’re getting only about half of the factor return.

Moreover, the value factor seems to be trending down, as this plot of its 20-year annualized return shows (Figure 2.2).

FIGURE 2.2 Twenty-year trailing returns of the small-stock and value-stock factors

Source data: Kenneth French Data Library

When we look at the 20-year trailing returns of stocks themselves—small value stocks, large value stocks, and total market portfolios—we see much the same pattern: both value portfolios’ superior prior returns seem to have disappeared (see Figure 2.3).

FIGURE 2.3 Twenty-year trailing returns of large value, small value, and total market portfolios

Source data: Kenneth French Data Library

There are two possible explanations for the recent disappearance of the value factor. The first is that as more investors became aware of value stocks’ superior historical returns, and as mutual funds and ETFs have made them more widely available, their prices have gotten bid up to the point that their expected return advantage has disappeared—what financial economists call a “crowded trade.”

When I wrote the first electronic version of The Intelligent Asset Allocator almost 30 years ago, getting exposure to value stocks, especially small value stocks, was difficult. For example, when in the 1940s the legendary investor John Templeton decided to put together a portfolio of small company stocks, he had to call in favors from his brokerage firm contacts to purchase the shares individually from their scattered owners. This was well worth his effort, as his portfolio quadrupled over the next four years.

As late as the mid-1990s, concentrated retail exposure to the value and small factors was available mainly from one fund family: Dimensional Fund Advisors. The company, associated with professors Fama and French, made its funds available only to the clients of certain investment advisors. Since then, retail and institutional investors have much easier access to value stocks and perhaps bid up their prices. Had this actually happened, the valuation gap between value and growth stocks would narrow—that is, value stocks would get more expensive relative to growth stocks.

The alternative explanation for value stocks’ recent underperformance is that investors have been dazzled by the growth prospects and monopoly power of the big tech firms, which are almost exclusively large growth stocks, and have “dumped” their value stocks to purchase these high flyers, a dynamic that partially reversed in 2022. (I’ll admit that the verb “dump” or even “sell” is inaccurate. What actually happens in this case is that value-stock sellers must lower the price they’ll accept in order to coax buyers out of the woodwork.)

Choosing between these two explanations for the recent disappearance of the value premium—increasing popularity bidding up value stock prices versus investors irrationally selling them off—is a snap. The first explanation should see value stocks get more expensive relative to growth stocks, whereas the latter explanation would see them getting cheaper.

The data clearly favor the second explanation. Value stocks have in fact been sold down to a level that will likely produce superior future returns. Kenneth French’s online data library sorts the price/book ratios of US stocks into deciles. The top three deciles of this ratio define growth stocks, and the bottom three deciles define value stocks. Most of the time, growth stocks are about four times more expensive by price/book ratio than value stocks. By contrast, in 2020, growth stocks were 11.1 times more expensive than value stocks. This ratio fell to 8.7 in 2021 as value stocks outperformed growth stocks in that year, and yet again to 7.4 by November 2022. Figure 2.4 paints a clear picture of what’s happened in the past decade.

FIGURE 2.4 The value spread over time

Source data: Kenneth French Data Library

The last time the value spread rose this high was during the dot-com bubble of the late 1990s, and before that, during the Great Depression. On both occasions, the value factor proved generous to investors, as can be seen in Figures 2.2 and 2.3.

Some observers complain that the price/book ratio is obsolete, since the digital era renders a corporation’s physical assets increasingly irrelevant. Though true, a company’s book value is the most stable of its balance sheet metrics. Moreover, sorting companies by cash flow and earnings and calculating the ratios in the same way—the top 30% divided by the bottom 30%—finds the same value spread pattern as with price/book ratio, with the same high values seen at the top of the dot-com mania in 2000:

Value Spreads (Ratio of Growth: Value Metric)

Source data: Kenneth French Data Library

French’s data show similar returns patterns abroad: a large market factor return, a nonexistent small factor return, and a middling value factor return. For developed foreign markets from mid-1990 to end-2021:

Source data: Kenneth French Data Library

And for emerging markets from mid-1989 to 2021:

Source data: Kenneth French Data Library

Just as in the United States, the excess returns to small and value stocks have fallen recently. In developed foreign markets over the 10 years ending in 2021, they have become negative (−1.42% for the small factor and −3.74% for the value factor), while in emerging markets they remain positive, but still much smaller than in the past (+0.81% for the small factor and +2.56% for the value factor).

THE FACTOR ZOO

Over the past few decades, Fama, French, and other researchers have plumbed the rich data from CRSP and other sources for additional factors that predict return. Decades ago, for example, it became well known that stock prices exhibited momentum. High returns over the past year predicted slightly higher returns in the next year. Portfolios sorted on momentum in the same way as value (top and bottom three deciles) show that since 1927, the high-momentum stocks had returns 7% higher than the low-momentum stocks.

This finding mystified believers in the efficient market hypothesis (EMH). How could high-momentum stocks be riskier than low-momentum ones? In 2009, the risk finally appeared. Between December 2008 and January 2010, a momentum strategy that held the previous year’s high-momentum stocks and shorted the low-momentum ones lost 57.5% of its value. Further, as with the value factor, the overall returns of momentum have been negative for the past two decades. Momentum investing has an additional problem: it requires near constant portfolio turnover, and the attendant transactional costs may overwhelm any profits.

The 2009 “momentum crash” is a good example of how the “risk” in risk factors can remain hidden for a long time before it ambushes investors. Before 2009, many portfolio managers looked at momentum as a free lunch that could be gorged on ad libitum, but that year they found out that the risk was real.⁴

This raises a larger question. Is the same thing true of the most important returns factor of all, market exposure? Financial economists often speak of the “equity premium puzzle”—exactly why stocks have returns that have greatly exceeded those of bonds and bills.

Is it possible that, like momentum, the high-equity premium hides the small probability of a rare but large loss? The answer is probably “no.” In the first place, it’s hardly a secret that real equity returns can be negative for a very long time. Even in the best-case scenario, the US market, the real return was zero over the 17 years between January 1966 and January 1983. Next, a quick glance at Austria and Italy (at the bottom of Figure 1.5) shows demoralizing real returns of not much more than 1% for 122 years. (But even these tiny real returns far surpassed the inflation-related confiscation wrought by their bills and bonds.) If today’s investors do not appreciate the nature of the equity risk premium, it’s because they’re amnesic, in denial, or in need of an optometrist. For those with eyes, equity risk is anything but hidden.

Beyond Fama and French’s three classic factors—market, small, and value—there are others that seem to yield excess returns as well. The two found, for example, that companies that invest sparingly in R&D, acquisitions, and expansion do better than companies that spend aggressively on them. Since 1964, this “conservative minus aggressive” factor has returned 3.13%. Fama and French also found that since 1964, the most profitable companies have returned 2.63% more than the least profitable ones.

The more researchers look for returns factors, the more they find. Finance academics have gotten a little jaded with all this. Duke University’s Campbell Harvey identified hundreds of factors, disparagingly referring to them as the “factor zoo.” He rightly worries that many of these factors are the result of what’s known as “data mining.” One researcher, for example, perused a large UN database and found that butter production in Bangladesh accurately predicted the movements of the S&P 500. (The author mischievously titled his article “Stupid Data Miner Tricks.”)⁵

Harvey also expressed concern that investment company mendacity drives much of this research. In his words:

The rate of factor production in the academic research is out of control. We document over 400 factors published in top journals. Surely, many of them are false. . . . Many of the factors are simply lucky findings. The backtested results published in academic outlets are routinely cited to support commercial products. As a consequence, investors develop exaggerated expectations based on inflated backtested results and are then disappointed by the live trading experience.⁶

So how much should investors expose themselves to any of these factors? In the first place, it’s obviously not possible for all investors to do so, since in the aggregate they own the overall market, and they all can’t own only a limited segment of it. If indeed certain factors produce above-average returns, then we can’t all live in Lake Wobegon.

In the long run, there’s nothing wrong with not tilting toward any factors at all—that is, owning only total-market funds. These incur virtually no investment costs and are highly tax efficient.

Last, the only factor for which there’s both compelling supportive data and a believable theoretical and behavioral explanation is the value factor. I’m particularly impressed with the current high value spread. If forced to bet one way or another on the value factor, I’d go for a modest amount of exposure. But as with anything else in investing, at best you’re paid for taking risk, and that risk just might show up.

As a practical matter, it’s not possible for all but the largest individual investors to custom-design their own factor exposure; you’re going to employ a mutual fund company to do it for you. In the last chapters we’ll discuss the available products.

DEEP RISK: THE ONLY RISK THAT REALLY MATTERS

Saving and investing are nothing more and nothing less than the deferral of present consumption for future consumption, which, as repeated many times in these pages, requires thinking in inflation-adjusted (real) returns. Unless you’re near the end of your life, that consumption will occur decades in the future. Risk comes in two flavors: “shallow risk,” a loss of real capital that recovers relatively quickly, as has repeatedly occurred in the United States, the United Kingdom, and in many of the world’s other developed nations; and “deep risk,” the permanent loss of real capital.

At a minimum, sailing through shallow risk mandates deep liquidity. Without substantial safe, liquid reserves—for the average individual, Treasuries and CDs—you will not have the wherewithal to weather turbulent markets, purchase stocks at low prices, and keep your courage up when it’s needed most. Assets that look safe in normal times, such as corporate and municipal bonds, often head south when the sky darkens.

What defines the “depth” of risk? Two dimensions, the size and duration of losses, approximately:

Risk Depth = (Size of Real Loss) × (Duration of Real Loss)

The preceding formula is thematic, not mathematical. In other words, financial risk should be measured both in magnitude and in duration. For most investors, a good working definition of deep risk is a portfolio loss that is both big enough and lasts, for example, long enough to impair an otherwise apparently secure, planned retirement—perhaps a fall in value of more than half in inflation-adjusted terms that lasts for a generation.

In the United States the worst example of deep risk in a major asset class wasn’t the Great Depression, which saw stocks fully regain their peak 1929 purchasing power after 15½ years, but rather the 40 years between 1941 and 1980, during which the nation’s worst period of sustained inflation and an attendant dramatic rise in interest rates savaged bonds. Over those four decades, an inflation-adjusted dollar invested in long-term government securities fell in real value to 34 cents.

Over the past century, capital markets outside the United States are replete with examples of deep risk: the poor returns of bonds and bills in several European nations in Figure 1.5 in Chapter 1, which were the result of the hyperinflation seen during both world wars, the closures of the Russian and Chinese markets after their respective revolutions, and the Argentine government’s confiscation of retirement assets in 2008.

The biggest risk to your retirement portfolio, and especially to the assets you’re leaving to your heirs, is not the shallow risk of severe but temporary market declines, but rather of long-lasting or permanent loss of capital. Broadly speaking, the four horsemen of deep risk are, in decreasing order of probability:

1.   Inflation. Over the broad span of economic history, this has been by far the most common cause of permanent loss of capital. The number of nations that have had to redenominate their currencies over the past century far outnumbers those that have not. Only a few currencies in existence in 1900 have not been redenominated, and fewer still—the US dollar, pound sterling, and Swiss franc—will a single unit of purchase even a small item today.

2.   Confiscation. Depending on your ideological bent, taxes are either outright theft or the club dues necessary for a functioning society. In extreme cases, however, the loss can be outright and total.

3.   Devastation. War and revolution can destroy an economy, even when a nation’s institutions allow for rebuilding productive capacity, as occurred in western Europe after both world wars. In most such cases, inflation and the necessary recapitalization of industries devastate security returns. In a world of increasing nuclear proliferation, the worst case produces scenarios in which your portfolio will be among the least of your problems.

4.   Deflation. Before central banking and the twentieth century’s abolition of hard money, deflation occurred fairly often. In the era of the monetary printing press, this is now the least likely scenario. Even in the most commonly discussed contemporary example, Japan, inflation has been positive, if just barely (0.44% annually since 1990).

Let’s take these four horsemen of deep risk in reverse order. In the modern era of fiat money, deflation is extremely rare, and there’s not much you can do, at least financially, about devastation.

The only sure way to avoid confiscation is to move both yourself and your assets abroad. Do you really want to depart the country of your birth, friends, and family? Gerard Depardieu may have been willing to relocate from France to Russia to avoid France’s high marginal tax rate, but in 2023 not many other rich Frenchmen want to join him there.

Most US citizens are loath to renounce their citizenship. If they do, they may pay substantial expatriation taxes. A halfway measure is to retain citizenship but move assets abroad. Americans who own stocks and bonds at foreign brokerages will encounter a barrage of IRS red tape and legal risks. The safest assets to own abroad are ones that produce no income, such as gold bars in a foreign vault or real estate that you don’t rent out. Even then, you’ll have to file a regular Report of Foreign Bank and Financial Accounts (FBAR) with the IRS. The rules change with some frequency, so you’ll need regular consultations with an accountant specializing in expatriate taxation. Still, if you have always wanted to own a flat in Paris or Florence, you now have one more reason to buy one.

Although I view expropriation as a significant long-term financial risk, I cannot personally imagine moving abroad nor enduring the hassle and risk of moving assets abroad. If I were a citizen of Israel, South Korea, Hong Kong, or almost any underdeveloped nation, my opinion might be different. I do occasionally dream of owning a Tuscan villa, but renting one, even regularly, pencils out better than owning and is much less of a hassle.

The most easily managed deep risk is the first one, inflation, which is fortunately both the most likely risk and the one simplest to mitigate. First, keep your nominal fixed-income maturities short: preferably less than five years. Not only does accelerating inflation hurt longer bonds the most, as happened in spectacular fashion in 2022, when the 30-year US Treasury lost 30% in total return, but as we shall see in Chapter 3, inflation increases the stock/bond correlation, which tends to magnify stock losses. (Long-term government bonds do provide the best defense against deflation, but inflation, which destroys their value, is far more likely.) Treasury Inflation Protected Securities (TIPS) or I bonds in small amounts in a taxable account are also useful inflation-fighting tools.

Though it’s true that stock prices fall as inflation rises, equities still represent a claim on real assets, and over the very long run, they seem to hold their real value. For example, during the Weimar inflation of 1920–1923, which saw consumer prices inflate by a factor of a trillion, equities produced significant positive real returns, though it was still a wild ride, as seen in Figure 2.5.

FIGURE 2.5 Stock performance during the Weimar hyperinflation of 1920–1923

Although the recent track record for commodities futures funds suggests that because of crowding/contango, they are a mug’s bet, the stocks of the commodities producers themselves can fare rather well during periods of high inflation, as seen in Table 2.1, which lists the returns of four asset classes for the 9 years since 1950 with inflation higher than 5%.

Table 2.1 Performance of stocks of commodity producers in high-inflation years (see text)

Source data: Kenneth French Data Library

This compilation needs a little unpacking. I selected the nine years in which inflation exceeded 5%, then calculated the annualized returns for each asset class as if those nine years had occurred in sequence (CPI = inflation/consumer price index, CRSP 1–10 = total US stock market).

Value stocks also tend to do relatively well during periods of high inflation for at least two reasons. First, they are relatively more indebted than growth companies and benefit as inflation erodes away the size of their debt. Second, their cash flows occur sooner than those of growth companies, so the present value of value stock cash flows get discounted less than those of growth stocks. Between 1975 and 1981, for example, the Fama-French US Large Value and Growth indices returned, respectively, 20.98% and 12.15% annually on a nominal basis, while the Fama-French international value and growth indices returned, respectively, 20.39% and 13.15% annually, during a period when US inflation averaged 8.86% per year.

CHAPTER 2 SUMMARY

Images   Value stocks—the shares of companies selling for low multiples of earnings, dividends, sales, and book value—have historically had higher returns than the market. Both behavioral and risk-based reasons explain this.

For the past two decades, this has not been true. This is likely because the prices of growth stocks have been bid up to unreasonable values, and the superior historical returns of value stocks seem likely to return. This assertion comes minus any guarantee. Value stocks may also be a good inflation hedge.

Images   Researchers have identified many factors associated with increased return, which may simply be the result of data mining and in any case may come attached to hidden risk. The average investor, by definition, owns the total stock market, and not everyone can or should tilt their portfolio away from it. In later chapters we’ll discuss just who might profitably do so and who should not.

Images   The most important financial market risk is not the occasional bear market that produces short-term decreases in wealth, but rather those economic and geopolitical events that can produce a generation-long loss of inflation-adjusted capital. Inflation, which can devastate the value of long-term bonds, is the most important of these risks.

CHAPTER 3

THE RECENT HISTORY OF RANDOMOVIA

In this book’s first edition, I transported the reader to the mythical country of Randomovia, a tropical paradise perfect in every way save one: an infestation of monkeys cursed its otherwise idyllic existence.

Quite by accident, Randomovia’s inhabitants stumbled across an ingenious solution to the monkey surplus: they taught them how to select equity portfolios by throwing darts at the newspaper’s stock page.¹ The market-addled animals soon lost interest in sex and their numbers plummeted.

Three things immediately became apparent to the Randomovian Bureau of Simian Finance:

Images   Purely by chance, some of the monkeys outperformed the market return by a wide margin. In any given year, a few even posted triple-digit returns, which attracted wide notice in the Randomovian financial press; monkeys that did poorly got ignored.

Images   On average, one year’s performance had zero influence on the next year’s, though a few simians had years-long lucky streaks before flaming out.

Images   On average, the monkeys didn’t beat the market. How could they? They were all throwing darts at the same page.

This chapter’s message couldn’t be simpler: welcome to Randomovia.

***

The first person to discover the random nature of financial markets was an obscure Frenchman named Louis Bachelier, the scion of a late-nineteenth-century French bourgeoisie family, his father a Le Havre wine merchant and his mother a poet from a banking family. He aspired to be a mathematician, but the early deaths of his parents forced him to take over his father’s business to provide for his younger siblings. After a few years, he sold the firm and moved to Paris, where he found employment on the Bourse before finally making his way to the Sorbonne to study under the great mathematician Henri Poincaré.

In 1900, he successfully defended a doctoral dissertation, Théorie de la spéculation, inspired by his experience on the Bourse. His thesis presaged a theory made famous by Einstein several years later: Brownian motion, the random movement of particles suspended in a medium.

The dissertation’s prescience takes the breath away. For example, it predicts that the market’s random motion increases as the square root of time. If the market shows 1% volatility over one-day periods, then over successive four-day periods volatility will be 2%—the same relationship Einstein later derived for Brownian motion. Even more relevant was his description of what happens when well-informed, speculative traders transact: “The mathematical expectation of the speculator is zero” (italics original).²

The Great War further interrupted Bachelier’s academic career, which sputtered along for three more decades before he died in 1946 at age 76. Along the way he published a popularization of his work that sold several thousand copies, but he remained obscure until an unlikely daisy chain of events earned him a hallowed place in modern finance. Ironically, it began with a Soviet mathematician named Andrey Kolmogorov, who pointed out Bachelier’s work to a French mathematician, Paul Lévy, who brought it to the attention of an American, Leonard Jimmie Savage (whom Milton Friedman labeled “one of the few people . . . whom I would unhesitatingly call a genius”).

In the early 1950s, Savage sent postcards to multiple economists that said, in effect, “You’ve got to read this guy!” One of the recipients was Paul Samuelson, an immensely gifted economist who improved on Bachelier’s options-pricing formulae, which eventually sparked the interest of two of his students, Myron Scholes and Robert Merton. The two went on to use those insights to garner their Nobel Prizes and (you guessed it) found Long-Term Capital Management.

Samuelson never forgot Bachelier’s assertion that speculation carries a zero return. In the 1974 inaugural edition of The Journal of Portfolio Management, he published an article titled “Challenge to Judgment,” in which he suggested that the Frenchman’s insights could be put into action if “some large foundation set up an in-house portfolio that tracks the S&P 500 Index.”

The piece was read by a young mutual fund executive named John C. Bogle, who at that moment was fighting for his professional life.³ The rest, as they say, is history, and besides, we’re getting well ahead of that particular story.

Around the time that Bachelier was toiling in the groves of academe, Alfred Cowles 3rd, the wealthy grandson of Chicago Tribune owner Alfred Cowles Sr., was getting his fingers dirty in the financial markets that the Frenchman had theorized about. After he graduated from Yale in 1913, tuberculosis sent him to a sanatorium in Colorado. With time on his hands, he began dabbling in the family’s finances, which suffered, along with everyone else’s, in the ferocious bear market that ground on for nearly three years after the 1929 crash that eventually battered stock prices down by almost 90%.

This financial disaster was unforeseen by virtually everyone, including Cowles, who was an enthusiastic reader of financial newsletters. Recall the danger-strewn highway of riches metaphor from the Introduction. The Cowles family fortune had skidded off that highway on one of its most dangerous curves: the market guru ice patch. Cowles loved collecting data, and he soon was deploying the leading-edge computing technology of the era, the Hollerith punch-card machine, to crunch the newsletter service numbers. Eventually, he found his way to one of his father’s Yale professors, Irving Fisher, one of the best-known financial economists of the era.

Fisher, too, had been burned by the 1929 crash, and not just financially. Famous among academics as the inventor of much of modern financial theory, including the discounted dividend model described in the math box in Chapter 1, to his everlasting misfortune he is remembered in the public mind as the source of perhaps the world’s worst market-timing call, opining in the fall of 1929 that “stock prices have reached what looks like a permanently high plateau.”⁴

The combination of Cowles’s enthusiasm and money and Fisher’s academic horsepower and data access proved a godsend to the world’s investors, at least for those who were willing to listen. Fisher had already established an organization to collect financial data, the Econometric Society, but it struggled for funding—until Cowles came along.

Cowles became the guardian angel of the ambitious but poor Econometric Society and of the associated Cowles Commission for Research in Economics, which over the decades hosted the leading lights of economics.⁵ Cowles also helped launch Econometrica, the commission’s house journal, which almost instantly became one of the field’s top-tier publications. In a 1933 article titled “Can Stock Market Forecasters Forecast?” Cowles examined the prognostications of 16 financial service companies, the stock purchases of 20 fire insurance companies, and the market forecasts of 24 newsletters. Their recommendations were, on average, atrocious. Readers would have been better off throwing darts at the stock page.

At the end of his article, he transported his readers to one of Randomovia’s outer suburbs by randomly shuffling the 24 newsletters’ recommendations. This slightly improved their overall performance. The returns of the best random recommendations equaled the best of the actual recommendations, and the worst random ones were actually far better than the worst of the real-world examples. In 1944 Cowles extended the study for another decade and came up with identical results.⁶ The answer to the original article’s title question was a resounding “no.” Forecasters could not forecast.

For about a decade after Cowles’s 1944 article, the field of investment management performance lay largely fallow. In the late 1950s, Tufts University economics professor Harry Ernst hired the undergraduate Eugene Fama as a research assistant. Growing up in a working-class Boston neighborhood in the postwar years, Fama had originally majored in French, but with a young family to support he realized he needed better material prospects. He switched to economics, where Ernst put him to work looking for profitable trading rules. Fama uncovered an entire platoon of them, but Ernst, an experienced statistician, held back a large data sample from his young protégé. When he let Fama loose on the new data, his previously successful strategies fell flat. In the jargon of economics, while Fama’s “discoveries” succeeded ex post, they failed ex ante.⁷

These two quaint Latin phrases, which literally mean, respectively, “after the event” and “before the event,” are two of the most important in finance. Ex post is easy, ex ante is hard. Fama never found a strategy for Ernst that produced excess returns ex ante.

Why, then, was Fama so successful ex post, but not ex ante? Say you’re looking at 10 stock characteristics that might predict future returns. If you examine each separately, that’s 10 different factors to examine. But wait: combinations of two factors yield 45 possible strategies, and three factors yield 120.*

When you increase the number of factors examined, you get a nearly infinite number of possible strategies. The factors that Fama initially found for Ernst would have made them both rich, the data-mining problem we encountered in the previous chapter’s discussion of the “returns factor zoo.” Hindsight is 20/20; as put by Warren Buffett, “Beware of past-performance ‘proofs’ in finance. If history books were the key to riches, the Forbes 400 would consist of librarians.”⁸

Consider a stadium containing 10,000 people. Everyone stands and flips a coin; flip tails and you sit down. On average, after 10 flips, 10 flippers will remain standing. It’s the same for picking stocks and money managers. Start with enough strategies or mutual funds, and purely by chance some will shoot out the lights. That doesn’t mean they can turn the trick next time.

Fama soon arrived at the same conclusion. In the long run, almost no one can time the market or pick winning stocks. Lady Luck alone dictates that some market-timing strategies or mutual fund managers outperform the others, but eventually the law of averages plays the grim reaper. Someone always wins the coin-flipping game, but they’re still going to flip heads only half the time on subsequent tosses.

Fama went on to a long and distinguished career at the University of Chicago, where he became best known for the efficient market hypothesis (EMH), which states, more or less, that the financial markets incorporate all known information into their prices.*

This means two things: first, stock picking is an expensive fool’s errand, and second, that only new information—that is, surprises—move stock prices. Since by definition surprises can’t be predicted, prices move in a purely random fashion.

The EMH rocked the world of finance. For starters, it consigned to the dust bin the field of “technical analysis,” a bogus technique that attempts to divine the future direction of stock prices from price movement patterns, using visual images such as “double-bottoms” and “head-and-shoulder” patterns to signal bottoms and tops. A cynic might say that technical analysts exist mainly to make astrologers look good.†

About the same time that Fama began to develop the EMH, investment manager Jack Treynor and academic William Sharpe decided to examine mutual fund managers for evidence of stock selection skill. The two had realized that investment performance had to be adjusted for the amount of risk taken—essentially stock exposure, which manifested itself in portfolio volatility. Sharpe’s research provisionally concluded that mutual fund managers weren’t measuring up. When he adjusted funds’ returns for their volatility, their average performance slightly lagged that of the Dow Jones Industrial Average. At the end of his article, he coyly suggested:

The burden of proof may reasonably be placed on those who argue the traditional view—that the search for securities whose prices diverge from their intrinsic values is worth the expense required. . . . Fortunately many who hold this view have both the means and the data required to perform extensive analyses; we will all look forward to their results.⁹

The investment industry, not much interested in committing the economic suicide implicit in Sharpe’s challenge, didn’t act on it, but in 1968, University of Rochester academic Michael Jensen did. Because most of the funds he examined held a significant portion of cash, almost all of them underperformed the market. So Jensen used sophisticated computer-based statistical methods based on Treynor and Sharpe’s mathematics to measure the performance of the funds’ stockholdings.

Figure 3.1 displays the performance of the funds’ stockholdings on a gross basis, that is, before the funds’ management fees are subtracted. The thin vertical black line shows the market performance. To the right are the 48 outperforming funds; to the left are the 67 underperforming ones. As predicted, the average performance was close to that of the market (actually 0.4% less than the market).

FIGURE 3.1 Risk-adjusted performance of mutual funds before fees

Source data: Michael Jensen, The Journal of Finance, 1968.

Figure 3.2 displays fund performance the shareholders actually got, after subtracting the funds’ management fees. The bars all shifted to the left and demonstrate only 39 outperformers versus 76 underperformers. Just 1 fund outperformed the market by more than 3% per year, while 21 underperformed it by more than 3%. Jensen’s results repeat the pattern seen in Cowles’s original work: no evidence of skill at the top of the heap, and at the bottom of the heap, the strong suggestion that some managers possess a special ineptitude.

FIGURE 3.2 Risk-adjusted performance of mutual funds after fees

Source data: Michael Jensen, The Journal of Finance, 1968.

Worse, all the mutual funds studied carried sales loads—a fee, typically 8.5% of the purchase amount—which Jensen did not take into account, so the funds’ investors obtained even lower returns than shown in Figure 3.2.¹⁰ In short, Jensen found precisely what you’d expect from a bunch of Randomovian chimpanzees:

Images   The average fund produces a gross return approximately equal to the market’s return.

Images   The average investor receives that market return minus expenses.

Images   Chance seems to explain the “best” managers’ performances.

If you think about it, it can’t be any other way. Professional money managers, for all intents and purposes, are the market, so by definition they must (on average) obtain the market return before expenses. Their customers get that return less expenses—what academic William Sharpe called “the arithmetic of active management.”¹¹

We haven’t quite arrived in Randomovia yet, since Sharpe and Jensen’s data still left open the possibility that their best performers’ high returns were due to skill and not luck. Since they published their research, literally dozens of studies have verified Bachelier’s intuition: past superior performance does not persist. (Regrettably, almost none of these subsequent studies are accessible to the lay reader. The late 1960s, when Jensen’s study was published in The Journal of Finance, was about the last time that the average college-educated person could get through an academic investing article without falling asleep. Ever since, the interpretation of financial research has required advanced statistical ability. To borrow a line from Mark Twain, the academic financial literature had become “chloroform in print.”)

Typically, these more recent studies reveal a brief, tiny persistence in performance. Last year’s top performers beat the average fund by perhaps 0.25% to 0.5% the next year, probably as a result of the momentum effect discussed in the last chapter. After that, nothing.

A single 0.25%–0.50% return boost in the following year is much lower than average mutual fund fees and expenses, so this strategy is futile. Over longer periods, even excellent past performance provides zero future benefit.¹²

Of the dozens of studies done on mutual fund performance persistence, the most optimistic found that, if you invested in the top 10% of last year’s funds, you would match (but not exceed) the performance of an index fund with low expenses in the next year. This “strategy” requires a near total fund turnover each year. This is the best-case scenario for actively managed mutual funds: turn your portfolio over once a year and you might match the index. And that’s before taxes. In a taxable account, this strategy would eat you alive with short-term capital gains, which are penalized at your full marginal federal and state rates.

Figure 3.3 displays the performance of all diversified US mutual funds followed by Morningstar, which includes S&P 500 index funds, over the 30 years between 1991 and 2020, divided into six 5-year periods. For this period, I identified the top one-quarter of funds and compared their performance over the next five years with that of the average fund and the S&P 500.

FIGURE 3.3 Nonpersistence of prior top-quartile Morningstar diversified US mutual funds

These results show zero evidence of persistent fund manager skill. In three of the five subsequent 5-year periods, the average fund outperformed the previous top-quartile fund, as did the S&P 500. Over the full 25-year period between 1996 and 2020, the S&P 500 returned an annualized 9.56%, the average fund returned 8.90%, and the past top-quartile funds came in last at 8.63%.

Nor is this all: in an average year, about 3% of funds disappeared, usually because of underperformance. Killing off the worst performers makes the starting cohort look better than it should, an effect known as survivorship bias, which finance academics find overestimates the actual performance of active funds by about half a percent.¹³ In other words, even Figure 3.3 presents an overly optimistic picture of actively managed fund performance.

Figure 3.3 strongly suggests that the apparent outperformance of a given money manager is due to luck, rather than skill. When we slice and dice mutual fund performance in a different way by simply following quartile location forward from period to period, in almost every case, a fund in a given quartile in the prior period has an approximately 25% chance of being in each of the four quartiles in the next, which is exactly what you’d expect by chance alone.

Finally, as Cowles found, many studies of mutual fund performance do show a slight amount of persistence in one corner of the professional heap: the bottom. Money managers who are in the bottom few percentiles of their peer group tend to stay there because those who charge the highest management fees and who trade the most frenetically incur the highest costs, year-in and year-out. That is to say, performance comes and goes, but expenses are forever.

THE COLLECTIVE WISDOM OF THE MARKET

There’s a reason why the market makes monkeys out of money managers. It represents the collective wisdom of all its participants and is thus smarter than even the smartest individual ones.

This phenomenon was first noted by Francis Galton’s observations at the 1906 West of England Fat Stock and Poultry Exhibition in Plymouth, whose attendees were asked to guess the weight of a dressed ox. The average of their estimates was off by a single pound, more accurate than even the best single guess.¹⁴

The classic modern examples of collective wisdom involve a thermonuclear warhead lost in the Mediterranean in 1966 and the wreck of the USS Scorpion, which sank in the Atlantic Ocean in 1968. In both cases, the statistically averaged estimate by multiple experts of their locations was off by only 200 meters, which was better than the best individual estimate.¹⁵

The point cannot be made strongly enough. People who predict future market price movements assert that they’re smarter than the market’s collective wisdom, which is quite a boast.

SHOOTING STARS

The highway of riches is strewn with another kind of hazard: the superstar-manager pothole. Human beings are wired to respond more to narratives than to dry numbers and facts. The financial media understands this. It’s one thing to absorb convincing academic evidence that investing in actively managed mutual funds is futile; it’s quite another to withstand the nearly constant drumbeat of media coverage of the riches turned out by winning investment funds. So I’m going to tell you what the financial media doesn’t about its coverage of successful funds and managers: how these stories usually end.

The financial press is a shark circling in the water, constantly on the lookout for compelling narratives that will draw in eyeballs and advertisers, a voracious imperative that prevents financial reporters from serving up sensible information: purchase low-cost index funds and ignore every bit of news about the Federal Reserve or this week’s market gyrations—what journalist Jane Bryant Quinn labeled “financial pornography.” A useful rule of thumb is that financial headlines can be safely ignored, since anything that appears above the fold has already been impounded into prices. As Bernard Baruch supposedly said, “Something that everyone knows isn’t worth knowing.”¹⁶

Among financial journalism’s 50 shades of investment porn is the superstar fund manager story. As we’ve already seen, at any given time, purely by chance, one fund or another will shoot out the lights, and the star-manager genre is a hardy financial media perennial. As I was writing the first drafts of this book, the superstar du jour was Cathie Wood, the charismatic founder of ARK Investment Management. The ARK Innovation ETF (exchange-traded fund, symbol ARKK), turned in a blistering 61.2% annualized return from 2017 to 2020, handily outpacing the 16.05% annualized return of the S&P 500. Wood’s earnest pronouncements about the riches to be had from companies that deploy “disruptive technologies” still fill the financial media.

Sadly, 2021 was not as kind to her investors. That year saw the ARK Innovation ETF lose 23.6% (versus a 28.7% gain for the S&P 500). As usually happens, most of her investors were attracted by her spectacular returns and joined the party late, in 2020–2021. A study by Morningstar analyst Amy Arnott, titled “ARKK: An Object Lesson in How Not to Invest,” calculated that while the annualized return of the fund since its October 2014 founding was a sizzling 28%, the average dollar invested in it only got a 9.8% return, versus an annualized 14.4% for the S&P 500.¹⁷ Investors would have done well to have heeded the advice offered by Ms. Arnott in late 2021; in 2022, ARKK lost 67.0%, versus a 18.1% loss for the S&P 500.

Not that warning signs weren’t flashing long before that. Before founding ARK Investment Management in 2014, Wood had worked as a fund manager at AllianceBernstein, where she managed multiple funds that on average underperformed. Before that, she cofounded Tupelo Capital Management, which flamed out in the tech crash of the early 2000s.¹⁸ Even if you weren’t aware of Wood’s less-than-stellar prior money management career, likely the result of high cost and frenetic trading, the superstar fund manager genre serves up a generous dollop of George Santayana’s dictum, “Those who cannot remember the past are condemned to repeat it.”¹⁹

In 1943 a Harvard-trained lawyer named Edward C. Johnson II, with almost two decades of investment experience under his belt, bought the moribund Fidelity Fund, which had been founded in 1930 as one of the nation’s first mutual funds. (The fund continues to operate to this day.) A few years later he founded the Fidelity Management and Research Company, the predecessor of today’s behemoth Fidelity Investments. In 1952 Johnson hired a young Chinese immigrant named Gerald Tsai, whose ability, drive, and vision landed him a berth as the manager of the Fidelity Capital Fund. (Johnson, something of a maverick, appointed Tsai as a sole manager, an unusual move in a business where committees ran funds.)

Tsai’s specialty was growth-stock investing. During the mid-1960s, growth companies—Xerox, IBM, LTV, Polaroid—came into vogue. The Go-Go Years, as they became known, mirrored the internet bubble of the late 1990s and the recent infatuation with big tech firms, with valuations approaching those seen during the more recent enthusiasms.

Tsai was the prototypical “gunslinger,” in the argot of 1960s money management. He aggressively bought and sold stocks at a rapid pace and rang up attention-getting returns in the process. In the aftermath of the 1962 downturn, his Fidelity Capital Fund gained 68%. In 1965, it gained another 50%, versus only 12.4% for the S&P 500. Journalist John Brooks wrote that his trading was

. . . so swift and nimble in getting into and out of specific stocks that his relations with them, far from resembling a marriage or even a companionate marriage, were more like those of a roué with a chorus line. Sometimes, to continue the analogy, the sheets were hardly cool when he was through with one and on to another.²⁰

Tsai viewed Johnson as a father figure, but when the personable young Edward C. Johnson III joined the firm, Johnson père told Tsai that he was not in line to run the company, and Tsai left to found the high-octane Manhattan Fund.

At that point Tsai found himself in Randomovia. The years 1966–1967 were mediocre for the Manhattan Fund; in 1968, it flatlined. In the first half of the year, Manhattan lost 6.6% of its value while the market gained 10%. The Manhattan Fund was ranked 299th among the 305 funds tracked by mutual fund expert Arthur Lipper. Just before Manhattan bottomed, Tsai sold it to CNA Financial Corporation for $30 million.

What went wrong at the Manhattan Fund? The press spun a tale of speculation and hubris, followed by the inevitable rough justice—at least for the fund’s investors, some of whom had paid an up-front load of as much as 50%.²¹ Tsai eventually went on to a distinguished business career, ultimately becoming chairman of Primerica. But the media missed something far more important. The Manhattan Fund fell to what later became a pervasive destroyer of actively managed funds: asset bloat.

We’ve already come across this phenomenon with Wood. Let’s say you buy XYZ company stock. It is unlikely that anyone has noticed your order—millions of dollars’ worth of its stock trades every day, and your piddling order is absorbed without affecting XYZ’s price.

On the other hand, if you have $50 million to invest in the shares of a small company, or even $1 billion to invest in a large one, you now have a problem: you cannot execute your purchase without inflating the stock price, since not enough stock is available at the current price to meet your needs. To attract sellers, you must offer a higher price. The opposite happens when you sell a large block of stock.

If the essence of successful trading is to buy low and sell high, a mutual fund grown elephantine with hot money is inexorably forced to do the opposite. The resultant drag on performance is known as “impact cost,” and it can crater a large fund’s return.

Tsai was the first in a long line of superstar fund managers to suffer from this phenomenon. When he started, Tsai’s reputation attracted $1.6 billion to his fund—an enormous amount for the time. His subsequent successful business career suggests that he may have had truly persistent skill before it ran into the inevitable brick wall of impact costs. In effect, Manhattan’s shareholders paid a “Tsai tax” each time he bought or sold, which destroyed the fund’s performance.

A recent impressive example of superstar fund manager collapse syndrome was William Miller, director of the Legg Mason Value Trust, and who bested the S&P 500 for 15 straight years between 1991 and 2005. By the early 2000s, I admitted to being impressed: after all, the odds of flipping 15 straight heads is just 1 in 32,678.

Then over the next three years, asset bloat, the fund’s 1.75% expense ratio, and Lady Luck all combined to almost completely wipe out the previous 15 years’ fantastic performance, barely nudging beyond the S&P 500 by 0.57% annually between 1991 and 2008. When Miller ascended from comanager to sole manager of the fund, it held only $750 million in assets, and anyone who bought after 1993, at which point it held only $900 million, would have been better off in an index fund.

By 1998, the fund had ballooned out to $8 billion; over the next 10 years the fund lagged the S&P 500 by almost 4% per year.²² Worse was to come: by 2006, Mr. Miller had amassed more than $20 billion in assets, which he took over the cliff. In retrospect, Mr. Miller’s metronome-like outperformance between 1991 and 2005 mirrored that of the mortgage lenders he overweighted—Countrywide, Bear Stearns, Washington Mutual—whose shares rocketed in the years leading up to the 2007–2009 global financial crisis. After 2006, that same overweighting of mortgage lenders went into full reverse, taking Mr. Miller and his hapless investors with them.

The search for outperforming money managers is called by some the “great man theory of investing”: identify the “great man” and when he fails, search for the next great man. Jonathan Clements of The Wall Street Journal says, “I own last year’s best-performing fund. The problem is I bought it this year.”²³

MARKET GURU BLACK ICE

The highway of riches features another treacherous stretch, a catchall category of “one-hit-wonder” market strategists, who by sheer luck correctly predict a market crash but then keep their followers out of the subsequent bull market. The average mutual fund manager or stock-picking newsletter might nick your performance with poor selection, but an incompetent market timer can cause truly catastrophic damage by interrupting the long-term magic of compounding.

The prototypical one-hit wonder was a colorful newsletter strategist named Joseph Granville. As a young man, he wrote for the EF Hutton brokerage before striking out on his own in 1963 with a series of eponymous newsletters. Granville combined a few lucky bear-market calls in the early 1970s and 1980s with a showman’s flair to attain cult status. He dressed in a tuxedo; performed original, market-themed piano-and-song compositions; and once flew onto the stage suspended from a 100-foot wire. At his height, 13,000 readers paid $250 per year for his flagship Granville Market Newsletter. On January 6, 1981, he told subscribers to “sell everything and go short.” The Dow Jones Industrial Average reacted by sliding 2.4% in the heaviest trading volume ever seen to that point on the New York Stock Exchange.²⁴

Avoiding market crashes does not guarantee financial riches. You have to be equally adept at reentering the market—something that Cassandras don’t do particularly well. Granville’s pessimistic predictions kept his readers out of subsequent market recoveries. Newsletter analyst Mark Hulbert calculated that between 1980 and 2005, Granville’s recommendations lost 0.5% per year, versus a gain of 11.9% for the S&P 500.²⁵

Several days before the October 19, 1987, market crash, an obscure Shearson Lehman mutual fund manager named Elaine Garzarelli predicted its imminent collapse and became an instant celebrity. Newspapers splashed her curly-haired visage across their business pages, and hundreds of millions of dollars poured into her fund, which proceeded to grossly underperform the market over the next three years. In 1994, Shearson, in the words of a press release, “orchestrated her departure from the firm.” Undeterred, she opined in 2003 that “you don’t have to be nimble to time the market, you just have to pay attention.”²⁶

Finally, no list of one-hit wonders is complete without Nouriel Roubini, a respected academic economist who in 2006 correctly predicted that excessive debt buildup would trigger a global financial crisis. Like Garzarelli, the handsome face of “Dr. Doom” became a familiar presence to viewers around the planet. In June 2009, he espied another financial panic just around the corner and told a reporter for the Sunday Times (London) that “I’m 95% in cash.”²⁷ Between that interview’s publication and the end of 2022, the S&P 500 rewarded investors with a total return of 459%.

Recall Alfred Cowles 3rd’s 1933 study in Econometrica, “Can Stock Market Forecasters Forecast?” More recently, two finance academics, John Graham and Campbell Harvey, reprised Cowles’s work on newsletters in that article by studying the forecasting ability of 132 market-timing newsletters that offered 326 different strategies. Not one of the newsletter strategies proved consistently correct. However, the authors did find a very transient hot/cold hand phenomenon. Newsletters with very high or low returns over a few months tended to persist for a few more months, then quickly reversed, probably the result of the stock-momentum returns factor discussed in the last chapter, a phenomenon so ephemeral and scattered among newsletters as to be useless. Otherwise, as Cowles observed, the only real consistency was seen at the bottom of the pile: a few newsletters demonstrated preternaturally poor performance. Similar to Hulbert’s observations about Granville’s recommendations, Graham and Harvey found that one of Granville’s newsletters produced an astounding 4.9% annualized loss during a 12½-year period when the S&P 500 produced an annualized 15.6% gain.²⁸

When researcher Andrew Metrick repeated Cowles’s work on stock newsletters using advanced statistical tools, he found much the same thing. As with mutual fund managers, the scattered outperformers’ returns could be explained by chance and consequently did not persist.²⁹

The worthlessness of newsletters, and of market strategists in general, makes perfect sense. If you could successfully time the market, you’d keep the profits for yourself. You wouldn’t work for a mutual fund company, seek employment at a brokerage, or make yourself available to the media. And you certainly wouldn’t sell that information in a newsletter for $250 per year.

WHY NOT JUST BUY STOCKS ON YOUR OWN?

Mutual fund managers are mostly highly intelligent, well educated, and hardworking. They have deep, rich sources of company-specific information. Despite these advantages, they don’t beat the market for one simple reason: they’re all competing against each other, so on average they get the market return, minus their expenses—Sharpe’s arithmetic of active management.

But just because fund managers can’t compete successfully against each other doesn’t mean that they can’t take less well-informed retail investors to the metaphorical establishment most eventually wind up in: the cleaners. From the perspective of professional money managers, there just aren’t enough uninformed mom-and-pop stock pickers to help their overall performance. Whenever you buy or sell a stock, you must ask yourself who’s on the other side of your transaction. The best-case scenario is that it’s someone smarter, harder working, and better informed than you, or else a high-frequency trader who’s going to nick you for pennies each time you trade. In the worst-case scenario, you’re transacting with Warren Buffett or the CFO of the company whose shares you’re buying or selling. You’re playing tennis against an invisible opponent; most of the time, it’s Serena Williams.

There’s a bigger reason, though, why you shouldn’t run your own portfolio. No matter how many stocks you own, it won’t be properly diversified. In finance-speak, stock returns are positively skewed, which means that a very small number of companies produce the lion’s share of market returns. One researcher, for example, found that since 1926, the majority of companies underperformed T-bills and that the bottom 96%, in the aggregate, barely matched the T-bill return. In other words, just 4% of companies provided the entire equity risk premium.

The same study found that over very long time horizons, just 23% of random five-stock portfolios beat the market. Increasing the number of stocks helps; 37% of 25-stock portfolios and 43% of 100-stock portfolios beat the market before expenses were taken into account.³⁰

It’s not too much of an exaggeration to say that even matching the market requires that you find the relatively small number of needles in the haystack—the 4% of high-performing stocks. Better simply to own the whole haystack.

WHAT ABOUT PETER LYNCH AND WARREN BUFFETT?

EMH skeptics are quick to point out two of its most prominent exceptions: Peter Lynch and Warren Buffett, both obviously skilled money managers who convincingly outperformed the market over a long period.

Let’s start with Lynch. After serving as a summer intern at Fidelity in 1965, he was hired on full-time in 1969 as a stock analyst, rose to director of research in 1974, and took the reins of the Magellan Fund in 1977. At the time, it was an “incubator fund,” open to the public for a few years following its 1963 founding, during which few investors purchased it, then open only to Fidelity employees until 1981, when the public was allowed back in.

At the time, the incubator fund tactic was a common ruse in the fund world: establish a cohort of incubators, kill off or merge the laggards into the winner, then advertise the heck out of the best one’s performance. This is exactly what happened to the Fidelity Salem Street Trust, which merged into Magellan just before it reopened.

From mid-1981 to mid-1990, Magellan returned 22.5% per year, versus 16.53% for the S&P 500. While that 6% margin seems impressive, it’s not in the same league as Warren Buffett’s performance and just barely outside the bounds of pure chance and random variation.

These returns, turbocharged with Fidelity’s vaunted marketing muscle, drove massive inflows. Beginning with assets of under $100 million in 1977, Magellan grew to more than $16 billion by the time the overworked Lynch retired in 1990. More than a generation after his retirement, Lynch’s gaunt, white-maned presence is still among the most recognized in finance.

Lynch was out of the country in the days leading up to the 1987 market crash. That year, he underperformed the market by almost 5%, which threw his type-A work style into overdrive. He turned in good performances in 1988 and 1989.

His performance soon fell victim to asset bloat. If there is such a thing as stock selection skill, then the greatest profits should be made in the stocks of smaller companies that have scant analyst coverage—in Lynch’s case, names like Crown Cork & Seal, LaQuinta, and Congoleum. But the smaller the stock, the greater the impact cost for a given dollar amount of trading. In a desperate attempt to avoid these costs, Lynch was forced to focus on ever-larger companies and finally to spread his bets among a larger number of them. By the end of his tenure, he was buying Fannie Mae and Ford and held more than 1,700 different firms, effectively becoming an expensive index fund. Both of these compromises drastically lowered Lynch’s performance relative to the S&P 500 benchmark. Figure 3.4 vividly plots his decreasing margin of victory versus this index. During his last four years, he outperformed the S&P 500 by only 2% per year. Exhausted, he quit in 1990.³¹

FIGURE 3.4 Fidelity Magellan versus the S&P 500 under Peter Lynch

Warren Buffett’s track record astounds in a way that Lynch’s does not. Mesmerized at an early age by the stock market, he was blessed with a priceless exposure to Benjamin Graham at the Columbia Business School in 1950–1951. Graham, who gave Buffett the only A+ he ever awarded, initially turned down his job application at the Graham-Newman Corporation. With anti-Semitism rampant in the investment business in that period, the firm reserved its analyst positions for Jews, and Buffett returned to Omaha to work for his father’s brokerage firm. A few years later, Graham relented and hired him.

Following Graham’s 1956 retirement, Buffett returned to Omaha, where he operated a number of investment partnerships. In the early 1960s one of them began to acquire Berkshire Hathaway, a failing textile manufacturer, at an average of about $10 per share, into which Buffett gradually folded his other partnership holdings. Over the more than half a century between 1965 and 2021, Berkshire returned an annualized 20.21%, versus 10.52% for the S&P 500. That’s impressive enough, but as the Covid-19 pandemic demonstrated all too clearly, humans do not intuitively understand exponential math. Compounding 20.21% annual growth over 57 years turned each $10 share into one that’s worth just shy of half a million dollars.

Warren Buffett kept this outperformance going for far longer than Peter Lynch for three reasons. First, Berkshire’s asset bloat was purely internal, the result of successful purchases, not of hot money inflow. Second, Buffett is more businessman than fund manager. The companies he acquires are not passively held in a traditional portfolio; he becomes an active part of their management. Most modern companies would sell their metaphorical mothers to have him in a corner office for a few hours each month. Finally, Buffett enthusiasts are fond of pointing out that the float of premiums collected by the insurance companies he has favored functions as cheap leverage for Berkshire’s holdings.

Parenthetically, though Professor Samuelson was one of EMH’s first supporters and wrote a seminal plea for the establishment of index funds, he knew a good thing when he saw it. In 1970, just five years after Buffett acquired Berkshire, Samuelson came across the stock’s track record, recognized Buffett as the exception that proved the rule, and bought some Berkshire. Still, after John Bogle took up Samuelson’s challenge and established the first widely available index fund in 1976, Samuelson stopped buying individual stocks. (Before 1976, Samuelson was also smart enough to recognize that it was better to own an asset management company than to be one of its customers. Noting that “as there is only one place for a temperate man to be in a saloon, behind the bar and not in front of the bar,” he also bought the shares of a mutual fund management company his secretary had told him about.)³²

But even Buffett cannot defy the gravitational law of asset bloat. Figure 3.5 plots the trailing 5-year returns of Berkshire versus that of the S&P 500. Just as with Lynch, Buffett’s spectacular initial results sowed the seeds of Berkshire’s eventual fade: over the 20 years between 2003 and 2022, you’d have been very slightly better off buying an index fund. (For the period, the admiral class shares of Vanguard’s S&P 500 fund returned an annualized 9.79% versus 9.76% for Berkshire.)

FIGURE 3.5 Berkshire Hathaway 5-year annualized trailing returns versus S&P 500

In fairness, Buffett favors value stocks, which have had some rough sledding in the past few decades. In the math box I show how Buffett still manages to beat the market by a few percent, but by nowhere near as much as his late twentieth-century margins. Value investing has just recently come back into vogue; if this continues, Buffett, who good Lord willing turns 93 around the time of this book’s publication, still might have enough road ahead to open up his margin over the S&P 500 again.

MATH BOX

How to Properly Evaluate a Money Manager with Multifactor Regression

Over the 20 years ending 2022, Berkshire Hathaway’s 9.76% return fell short of the S&P 500’s 9.80%. However, Buffett is a value investor who seeks out the shares of unglamorous companies selling at a discount to their earnings, a style that has been out of favor over this period. A more appropriate benchmark might be the Russell 1000 Value Index of large value companies, which Buffett does beat by 9.76% to 8.83% over the 2003–2022 period.

There’s an even better way to evaluate fund manager performance: regression analysis, a tool available in statistical software and also as an Excel add-in. In 1992, Fama and French published a landmark paper demonstrating that an equity portfolio return could be explained by exposure to three factors: the overall stock market, a small stock factor, and the value factor. The small and value factors are long/short. The small factor owns the smallest five deciles of the stock market and sells short the biggest five deciles, while the value factor owns the cheapest 30% of the stock market by price/book ratio and sells short the most expensive 30%. The market factor is simply the return of the overall stock market minus the risk-free rate: the 30-day Treasury bill. Finance academics and practitioners can also employ other factors, most commonly ones for momentum, profitability, and capital investment, but to keep things simple I’ll only deploy the market, small, and value factors, obtained from Kenneth French’s online data library, to analyze Berkshire’s performance.³³

Figure 3.6 shows how the data are set up in Excel:

FIGURE 3.6 How to set up a three-factor regression in Excel

In this regression, Berkshire’s return minus the risk-free rate (BRK-RF) is an independent variable. For 1965, Berkshire stock returned 49.5% and T-bills returned 3.93%, so the independent variable BRK-RF has a value of 49.5% − 3.93% = 45.57%. This column is then regressed against the market, small, and value (also independent variable) columns.

To examine how Berkshire evolved over the years, I divided the 57-year period between 1965 and 2021 into three 19-year periods: 1965–1983, 1984–2002, and 2003–2021. Here are the outputs:

The market factor beta fell during the last period, presumably as Berkshire reduced its stock exposure. The recent market factor beta value of 0.77 correlates well with the fact that the company currently holds about 20% of its assets in Treasury bills and other cash equivalents.

Likewise, the small exposure beta has become strongly negative, indicating that Berkshire’s increasing size has forced it to concentrate on the very largest companies, similar to what happened to Lynch’s Magellan. Value loading has also fallen, presumably for the same reason. Finally, the adjusted R², which indicates the quality of the model’s overall fit, has risen as Berkshire’s portfolio has become more conventional over the years.

The most important column in the preceding table is the alpha, the percent by which Berkshire has bested the market after taking into account its exposure to the three return factors. This has steadily decreased since 1965. The Sage of Omaha is still beating the market, but by an ever-smaller margin.

FINALLY, TWO GUYS YOU’VE LIKELY NEVER HEARD OF

The point can’t be overemphasized: superstar managers sow the seeds of their own destruction simply by growing their portfolios too large. Buffett’s outperformance outlasted Lynch’s because while the former has not received capital inflows for more than half a century, the latter didn’t shut off the fire hose of cash that soaked Magellan. (Fidelity finally did so in 1997, then reopened the fund in 2008.)

Another fund manager who benefited from the absence of inflows was Wilmot H. Kidd III, the manager of Central Securities Corporation, a closed-end fund that bested the S&P 500 by 2.8% per year for nearly half a century before he stepped down at the end of 2021 at age 80. A closed-end fund is a portfolio that trades as a stock and, critically, cannot take on new money. This protected Central Securities, as it did Berkshire, from inflow-caused bloat. At the end of 2021, it held only $1.3 billion in assets, a small amount for a fund with such a remarkable record.³⁴

It turns out that there are managers who beat the market by even larger margins than Buffett and Kidd over long periods. As you might suspect, there’s a catch: they do not want publicity, and more important, they don’t want your cash. After all, were you able to crush the market by that much, you would have no desire to invest anyone’s money but your own.

The archetype of this rare breed of superinvestors is Jim Simons. Unlike Buffett, Simons didn’t start out obsessed by investing. After earning a PhD in mathematics from Berkeley in 1961 at age 23, he straddled the worlds of high-level academics and code-breaking at the National Security Agency (NSA) before founding the hedge fund Renaissance Technologies in 1982.

Simons’s approach could hardly have been more different from Buffett’s. Rather than analyzing individual companies in detail, he began by painstakingly digging out massive amounts of data from primary documentary sources and virgin electronic data, much of it seemingly unrelated to finance. He then brought in the skills of world-class mathematicians and data scientists to crunch these numbers.

His strategies fed off short-term price movements and in the process grossly violated the EMH, which says that current price moves have no bearing on future ones. His performance made Buffett look like a Little Leaguer. In the 31 years between 1988 and 2018, the Medallion Fund, the flagship of Simons’s Renaissance Technologies, achieved a breathtaking 66% gross return—39% even after the humongous fees he was able to charge.

After just the first five years, Medallion solved the asset bloat problem by booting its clients. Thereafter the fund became the exclusive preserve of Renaissance’s owners and employees. Medallion share owners possess the next best thing to the Federal Reserve’s keyboards. In 2016, Renaissance fired one of its employees, David Magerman, for airing in The Wall Street Journal his objections to the politics of Robert Mercer, Simons’s conservative partner. When Magerman sued the firm over his firing, it settled by granting him continued access to Medallion.³⁵

This story suggests what might be called Simons’s Law: the most talented investors quickly privatize their talents by shutting their portfolios to all but family and employees. If someone’s skilled enough to regularly trounce the market, they don’t want to manage your money.

CHAPTER 3 SUMMARY

All Models Are Wrong, But Some Are Useful

Let’s take a step back and draw some conclusions from our four success stories. Lynch, Buffett, Kidd, and Simons are all indeed skilled. But these four exceptions—and others, such as D. E. Shaw and George Soros’s Quantum Fund—no more make the case for selecting active managers than the existence of Powerball winners argues for buying lottery tickets, and they certainly do not suggest that you should start buying individual stocks yourself. Just because Stephen Curry can drain one three-pointer after another doesn’t mean you can make a living in the NBA.

Of the tens of thousands of money managers who have practiced their craft during the past few decades, only the tiniest handful have shown indisputable evidence of skill. This is hardly a ringing endorsement of professional asset management. Further, as we saw with Simons, the rational and supremely skilled trader wants to manage money only for themself—not for you.

Our eyes settle on Buffett, Lynch, Kidd, and Simons only in retrospect. The odds of picking these four out of the thousands of fund managers ahead of time are nil. For every one of them, there have been hundreds like Tsai and Miller: managers who excelled for a while, but whose performance flamed out in a hail of assets attracted by their initial success.

You still might luck out and find an outperforming manager, but the odds are against you. Picking active managers is like a shell game with 10 shells, under which are $10,000, $9,000, $8,000, $7,000, $6,000, $5,000, $4,000, $3,000, $2,000, and $1,000. By picking an index fund, you’re guaranteed an $8,000 payment. What would you choose?

* (10!/[8!2!]) = 45; (10!/[7!3!]) = 120

* The EMH comes in three flavors: strong, which posits that all information, public and private, has already been impounded into prices; semi-strong, which posits that only public, but not private, information has been impounded into prices; and weak, which posits only that past price action does not predict future price moves.

† Although often ascribed to Fama, Fred Schwed was the first to make the connection between technical analysts and astrology. See Fred Schwed, Where Are the Customers’ Yachts? (Hoboken, NJ: John Wiley & Sons, 2006), 37.

CHAPTER 4

THE PERFECT PORTFOLIO

Your Uncle Fred turns out to be a marvellous employer: kind, generous, and fair, but also demanding. One big downside to working for him is the annual coin toss. With ever more riding on each year’s heads-or-tails, a sense of dread intrudes as the day approaches.

Years pass. Your uncle notices your anxiety and makes you another offer. “You know, you now have enough assets that I’ll divide them in half and toss a coin for each.” Your first thought is, what, two coin tosses? No!

But as always, Uncle Fred is trying to teach you something, so you sit down and diagram out the four possibilities from tossing two coins:

The first and last outcomes produce the same result as tossing one coin: +30% and −10%. In addition, there are now two intermediate results of +10% (the average of +30% and −10%). The odds of losing money have thus fallen from 50% with one coin toss to 25% with two.

This seems like a pretty good deal, but to be sure, you pay another visit to your old statistics professor, who reacquaints you with the concept of standard deviation (SD), which measures volatility. The SD for Uncle Fred’s single coin toss is 20%; for his two-coin toss, it falls to 14.1%. Even more surprisingly, the expected annualized return has increased from 8.17% for the single toss to 9.08%; you enthusiastically accept Uncle Fred’s offer.*

MATH BOX

The Pluses and Minuses of Standard Deviation

About seven decades ago, finance academics adopted the SD of returns—their volatility—as the main proxy for risk. Generally, this works pretty well. Without getting too deeply into the weeds, scholarly types assume that security prices behave the way that Bachelier and Einstein described as an unpredictable random walk, in which volatility increases as the square root of time.

While SD/random walk is a decent approximation of real-world security prices, it’s not perfect, something that Fama and a mathematician named Benoit Mandelbrot realized more than a half-century ago. Price movements instead more closely follow something called a “power law,” which postulates a negative linear relationship between the logarithms of event frequency and severity, as do earthquakes, terrestrial meteorite strikes, and terrorist events.

For investment purposes, SD has a more prosaic (and critical) limitation: it doesn’t take into account when volatility happens—what we called Ilmanen risk in Chapter 1.

To demonstrate this, I first examined the returns and risks of U.S. Treasury and corporate bonds. The first two rows in the following chart are the returns and SDs of the Bloomberg indices for intermediate-term Treasuries and intermediate-term corporates, respectively, with an average maturity of roughly six years.

The intermediate corporates have a return that is almost a full percent higher than the Treasuries, in compensation for the corporates’ default (credit) risk, which we described in Chapter 1: companies can default on their debts; Treasuries, at least in theory, should never default.

Intermediate corporates, for a number of reasons, have a higher SD than intermediate Treasuries, so to allow an apples-to-apples comparison between corporates and Treasuries, in the third row I created a 39.5%/60.5% mix of intermediate-term (about 6 years maturity) and short-term (about 2.5 years maturity) corporates. I chose this 39.5%/60.5% mix to exactly match the 3.94% SD of intermediate Treasuries.

Let’s see what happens when we dilute out the total US stock market with either intermediate Treasuries or the intermediate/short corporate mix, which has the same SD as the Treasuries. For this exercise I used the CRSP 1–10 index, which includes not only large S&P 500 companies, but also smaller ones. (See Figure 4.1.)

FIGURE 4.1 Mean-variance plot of US stocks with intermediate-term Treasuries and corporate bonds, 1976–2021

Source data: Kenneth French Data Library and Bloomberg

This is a mean-variance plot, with portfolio return on the y-axis and SD on the x-axis. (The “mean-variance” term is a historical artifact. Decades ago, economists preferred to talk about variance, which is the square of SD.) Return increases as we go up the y-axis; risk increases as we move to the right on the x-axis.

As you can see, there’s not a lot of difference between using corporates and Treasuries for your bond allocation in terms of return and SD, except at the low-equity region at the bottom of the curve, where the corporate mix offers a higher return at the same risk level as Treasuries.

Corporates can be thought of as Treasuries with some equity risk and return added in. Each of the diamond- and square-denoted data points represents a change of 5% in the stock/bond mix. It turns out that the 100% corporate mix has almost exactly the same return and SD as a 90/10 mix of Treasuries and stocks. To demonstrate this a little more clearly, I’ve enlarged the lower left corner of Figure 4.1 to create Figure 4.2.

FIGURE 4.2 Enlarged low return/risk area of Figure 4.1

Source data: Kenneth French Data Library and Bloomberg

Mean-variance plots like Figure 4.1 and 4.2 provide investors with a useful way to visualize the behaviors of both individual assets and complex portfolios. But they come with a dangerous embedded assumption: that up and to the left is always better. In finance-speak, this assumption means that the investor is “mean-variance preferenced.”

The trouble is that flesh-and-blood people aren’t mean-variance preferenced. They are human beings who tolerate losses in normal times better than they tolerate losses when the world is going to hell. Although the 100% short-intermediate corporate bonds and a 90/10 portfolio of intermediate Treasuries/stocks have nearly identical returns and SDs for the 46 years between 1976 and 2021, the former produced a great deal more stomach acid when it counted the most. In the teeth of the worst financial crisis in two generations, during September to October 2008, the corporate mix lost 8.04%, while the 90/10 intermediate Treasury/stock mix lost only 1.42%.

For those of you who skipped the math box, here’s the short version. As discussed in Chapter 1, the most common statistical definition of risk is volatility, as measured by standard deviation (SD). But SD misses an important dimension of risk: volatility timing. A portfolio of corporate bonds and another of Treasury bonds might have the same volatility, but the former will likely bite you hard during a financial crisis, when your hunger for cash will be most acute, whereas the latter can save both your financial and emotional bacon.

The story of Senator Richard Burr (R-NC) lays bare the emotional atmosphere of a financial panic. After the senator heard testimony in late 2008 from Treasury Secretary Hank Paulson and Fed Chair Ben Bernanke that the banking system had become so frozen that financial institutions could not move money among themselves, he called his wife and told her,

“I want you to go to the ATM machine, and I want you to draw out everything it will let you take. And I want you to go Sunday.” I was convinced on Friday night that if you put a plastic card in an ATM machine the last thing you were going to get was cash.¹

Were the good senator sitting on a nice comfortable pile of Treasuries instead of cash in a banking system that seemed on the edge of failure, he likely wouldn’t have made that phone call to his wife.

I have my own memories of this period: conversations with advisors at the end of their tether who couldn’t handle the 3 a.m. phone calls from frantic clients wanting to sell all their stocks, businesspeople faced with ruin when their normally reliable credit lines dried up, journalists and teachers who doubted that their 401(k)-funded retirement account would ever recover, and seemingly prosperous neighborhoods suddenly thick with foreclosure notices.

I weathered the stock carnage of 2000 to 2002 with relative equanimity and considered myself both quantitatively and emotionally prepared for yet another halving of my equity holdings. But as the global financial crisis of 2008 unfolded, I still considered the bonds of companies like Johnson & Johnson and Procter & Gamble worth 100% of face value. As in 2000 to 2002, I wasn’t particularly surprised when equities lost 50% and more. What did rattle me was that in order to purchase stocks at the fire sale, I had to suffer a haircut on some of my bond holdings. Few sensations are as disturbing as the realization that what you thought was money isn’t.

A great deal of your long-term success depends upon how you behave during the worst of times. Charlie Munger, Warren Buffett’s Berkshire partner, famously observed that the prime directive of compounding is to never interrupt it. Investors most often break that rule by losing their nerve when the chips are down.

SD and mean-variance plots don’t capture this essential element of risk: bad returns in bad times. The most dangerous stretches along the highway of riches are the mountain passes of bear markets. How carefully you drive through them will likely determine whether or not your portfolio arrives safely at your future self. A healthy dollop of Treasury securities are the investing equivalent of observing the speed limit on studded tires. Warren Buffett keeps roughly 20% of Berkshire Hathaway’s assets in T-bills and cash equivalents. That’s not a bad rule to follow.

MATH BOX

How Stock Prices Really Behave

Almost as soon as Bachelier published Théorie de la spéculation, researchers noticed that security prices varied by much more than a random walk process predicted. The distribution had “fat tails,” a fact Fama and Mandelbrot conclusively demonstrated in the mid-1960s.²

The US stock market’s SD is normally in the range of about 15%–20%, which implies a daily SD of around 1%. (That’s approximately the preceding range divided by the square root of the number of trading days in the year.) On October 29, 1987, the various market indices fell by more than 20%—that is, a −20 SD event. This clearly departed the Gaussian distribution implicit in a random walk. In my spreadsheet, a −20 SD event occurs at a frequency of 3 × 10⁻⁸⁹, a negative exponent larger than the estimated number of protons in the universe, of which there are only 10⁸⁰.

The power law states that the logarithms of probability and of severity are negatively and linearly related. This relationship better predicts the much higher frequencies of severe events than the very low estimates from the Gaussian normal distribution that defines random walk.³

FIGURE 4.3 Power law plot of daily Dow Jones Industrial Average price changes, 1926–2012

Figure 4.3 plots the power law distribution of the Dow Jones Industrial Average’s daily returns from 1926 to 2012. This graph needs more than a little unpacking. The x-axis plots the natural logarithm of each degree of loss expressed as percentage points. For example, a loss of 3% is plotted on the x-axis at ln(3) = 1.1. The frequency of loss is plotted on the y-axis; as a loss between 3.00% and 3.10% occurred on 23 of the 22,881 trading days of the 1926–2012 study period, its frequency was 0.10%, that is, 0.001. The natural log of this plots to −6.9 on the y-axis.

Note how relatively smooth and straight the data points in the upper part of the graph are. This is because relatively small losses occur relatively frequently and produce a well-behaved linear plot. The higher loss/lower frequency data points in the bottom part of the graph produce a much noisier plot, because there are far fewer of these events.

The bottom layer of points lie at a y-axis value of −10, which corresponds to a frequency of 0.0044% (0.000044). That frequency represents a single trading day in the 22,881-day study period, the biggest outlier being October 19, 1987. This relationship holds across multiple markets. In fact, curves for the US returns are similar to those of both the Japanese and Hong Kong stock markets.⁴

LOW SDS ARE GOOD, BUT LOW CORRELATIONS ARE BETTER

All this is not to say that the mean-variance framework isn’t useful. It’s good to increase return and decrease SD, as long as you first make sure you own enough truly safe assets to sleep at night.

Let’s return to Uncle Fred’s coin tosses. It turns out that the SD of returns for a given number of independent coin tosses decreases by the square root of their number. If Uncle Fred tossed a hundred coins, the coin toss SD would fall from 20% to just 2%, which would hardly raise your pulse.

When you pitch the hundred-coin toss idea to Uncle Fred, he chuckles. He doesn’t want to waste half a day tossing coins with you, and besides, it’s virtually impossible to find even two stock asset classes whose returns are completely independent of each other, let alone a hundred. Go back to work, he tells you.

Besides the SD, there’s another number you should understand: the correlation coefficient, often shortened to correlation. This number ranges from +1.0 to −1.0. It’s +1.0 when two assets always move in the same direction, zero when there is no relationship between the two, and −1.0 when they always move exactly opposite.

Let’s apply this to the two-coin toss example. If the tosses for each coin somehow always came out identically (a correlation of +1.0), the results would be the same as for the one-coin toss: an annualized return of 8.17% and an SD of 20. For a two-coin toss with a correlation of zero, the return rises to 9.08% and the SD falls to 14.1%.

Finally, in the improbable event that the two-coin tosses have a −1.0 correlation, so that heads for the first flip always comes with tails on the second, and vice versa, then the total return for each flip would simply be 10% (the average of +30% and −10%), and the SD would be zero. Too good to be true!

Here’s a best-case example of how diversification works in the real world. A portfolio consisting of half real estate investment trusts (REITs) and half S&P 500 is rebalanced annually for the eight years between 1995 and 2002:

Figure 4.4 plots these data.

FIGURE 4.4 Returns of S&P 500, REITs, and a 50/50 mix

Source data: Dimensional Fund Advisors

The return (the final amount on the right of the plots) of the 50/50 mix is higher than either that of the S&P 500 or of REITs. The 50/50 mix’s SD is lower than that of either asset: higher return with lower risk. What’s not to like?

A small confession: I cherry-picked an eight-year period during which the S&P 500 and REITs had approximately equal returns. Remarkably, the correlation of annual returns was −0.10, which turns out to be an anomalously low number for two different stock asset classes. Figure 4.5 plots the three-year rolling correlations between the S&P 500 and REITs over the past several decades. These graphs are for monthly returns. None quite make it below 0.0, as the annual returns did, and in any case, consider me pulled over by the data-mining police for choosing an S&P/REIT example during a period with anomalously low correlations.

FIGURE 4.5 Rolling three-year correlations of S&P 500 and REITs

Source data: Dimensional Fund Advisors

Many US investors also invest in international stocks as a way of diversifying. Here the news is even grimmer. Even during the earliest part of the period studied, correlations between US and international stocks were uniformly positive. Over the past decades they have risen to nearly 1.0, the point where they no longer seem to provide any diversification value.

FIGURE 4.6 Rolling three-year correlations of S&P 500 and international stocks (MSCI-EAFE)

Source data: Dimensional Fund Advisors

THE CURRENCY HALL OF MIRRORS

Foreign stocks or bonds subject investors not only to the intrinsic risks of those securities, but also to the additional risk of currency fluctuation. For example, a stock denominated in UK pounds sterling will rise or fall in value along with the value of that currency relative to the dollar. This currency risk can be eliminated (hedged) by selling forward a pound contract in the futures market.

Currency fluctuations can make a large difference in equity returns, but only in the short term. For example, between 1980 and 1985, the value of the world’s major currencies relative to the US dollar depreciated by about a third. During this period, although the prices of foreign stocks rose, currency losses ate up a significant portion of US shareholders’ dollar gain. The Plaza Accord of 1985 reversed this depreciation, which had the opposite effect: it augmented the subsequent dollar-denominated gains of foreign stocks. In other words, before 1985, American investors in foreign stocks benefited from hedging currency exposure; after 1985, currency hedging hurt them.

In the long run, currency effects have a tendency to mean revert. There’s another reason that they wash out as well. When a nation’s currency gains strength against the dollar, this makes its exports less competitive and lowers earnings, which tends to balance out any dollar-denominated share price rise.

In the end, a portfolio’s optimal degree of currency exposure is roughly equivalent to its foreign stock exposure. Investors should simply hold foreign stocks in unhedged vehicles, which is how the overwhelming majority of international stock funds operate.⁵ But they should hedge foreign bonds for the simple reason that currency volatility greatly exceeds bond price volatility. A hedged foreign bond behaves very similarly to a US bond. Because the bulk of your safe assets should carry a US government guarantee, this is largely irrelevant to your portfolio. Furthermore, since currency-hedged foreign bonds behave so similarly to domestic bonds, incur additional hedging expense, and don’t carry a US government guarantee, they’re not worth owning in the first place.

ASSETS WITH LOW CORRELATIONS WITH STOCKS

Investors diversify their stockholdings primarily with bonds that have low correlations with them. This low correlation, of course, comes at the price of lower returns. Figure 4.7 plots the rolling three-year correlations between the S&P 500 and intermediate Treasuries from 1973 to 2021.

FIGURE 4.7 Correlation between S&P 500 and intermediate Treasuries

Source data: Dimensional Fund Advisors and Bloomberg

The first half of the period corresponded to nearly two decades of high inflation, followed by the aggressive Federal Reserve’s response of monetary tightening by raising real interest rates. During this time, roughly the 1970s and 1980s, the correlation between the two assets was generally positive. A generation ago, bond prices seemed to drive stock prices: since bond prices move opposite to interest rates, when the Fed raised rates, bond prices fell, and stocks followed suit.

During the second half of the period, roughly beginning in the 1990s, investors were no longer afraid of inflation hurting their bond holdings. They fled into bonds when stock values dropped, particularly during the bursting of the internet bubble in the early 2000s and the global financial crisis of 2007–2009, and so the correlation turned negative. As a consequence, investors became comfortable with bonds as a safe harbor that mitigated the stock losses in their portfolios.

With the return of inflation in 2022, the pattern reverted with a vengeance back to the pre-2000 pattern of stock and bond prices moving in tandem, and bonds failing to provide a safe harbor from falling stock prices. In 2022, the S&P 500 fell by 18%, while the long Treasury bond fell by nearly 30% (which doesn’t show up in Figure 4.7 yet, since it plots 3-year rolling correlations).

CONTANGO AGAIN

Do any stock asset classes have persistently low correlations with the other major US and foreign equity markets? Precious metals mining companies certainly do. Between mid-1963 and the end of 2021, this asset class had a 0.23 correlation with the S&P 500.

“Gold bugs” prize the shelter that the yellow metal and its miners provide during financial crises. As might be expected, this protection doesn’t come for free; the insurance against geopolitical instability provided by gold and gold mining stocks bids up their prices and lowers their future returns. During this period, precious metals miners returned just 5.90%, better than T-bills (4.48%) but worse than 5-year Treasuries (6.36%), and far worse than stocks (10.70%).

How would you like an asset that has a −0.79 correlation with stocks? The VXX ETF, which tracks volatility futures like the VIX (the Chicago Board Options Exchange Volatility Index) does. When the markets plunge, the VIX rockets, and the VXX can save much of your bacon.

As you might expect, there’s a catch. These futures exhibit the “contango” described in Chapter 1, where futures prices are higher than the VIX index’s spot (or current) price. This means that, all other things being equal, the VXX ETF sells its futures contracts just before they expire at a lower price than they were bought.

The two-year period 2010–2011 showed just how expensive this process was. During those two years, the S&P returned the close-to-average annualized 8.4% and the VXX ETF suffered a loss of about 74%. The same thing happened to a lesser extent if you bought S&P put options. Yes, volatility options can protect you against market drops, but at a cost that more than wipes out the equity risk premium. You didn’t expect that someone would sell you bear market insurance for free, did you?

DOES DIVERSIFICATION EVEN WORK ANY MORE? THE PROBLEM WITH CORRELATIONS

The increasing correlations between domestic and foreign stocks shown in Figure 4.6 suggest that diversification among different stock asset classes is losing its value; indeed, everyday experience seems to confirm this. On days and in years when the S&P 500 does especially poorly, so too will almost all foreign stock markets. In the words of finance academic Bruno Solnik, “Diversification fails us just when we need it most.”⁶

In the short term, Solnik nails an essential truth. You can see it in the first two columns of the next table, which contains three columns of equity returns over three bear markets.

The first column demonstrates that during the bear market that followed the bursting of the internet bubble in 2000, seven of the nine listed stock asset classes suffered significant losses. Things were far worse during the 2007–2009 global financial crisis (second column), when all nine stock asset classes fell by more than half. REITs, one of the few bright spots in 2000 to 2002, fell by almost two-thirds during 2007 to 2009.

The last column shows bear market risk through a much wider lens: the decade between 2000 and 2009, which was the worst 10-year period in the modern history of broad global stock market indices, worse even than the decade following the 1929 crash. That decade saw both the 2000–2002 and 2007–2009 bear markets, but wide diversification into REITs and small and value stocks cushioned all the S&P 500’s losses and then some.

Total Returns (Nominal) During the Worst of Times: Three Perspectives

Source data: Dimensional Fund Advisors and Morningstar

How is it possible that this decade, which saw two deep bear markets with little or no shelter among different stock assets, also saw a whopping benefit to diversification? Simple. Spreading your stock bets around may be worthless during market meltdowns, but it proves its merit in the recovery from them. Wise investors care little about a horrendous year or two, as long as they can hang on through them. On the other hand, even the most disciplined investor can be ruined by a bad decade or two, and it’s over such very long horizons that diversification shines.

For example, consider a Japanese retiree who in the 32 years between 1990 and 2021 received a 0.53% nominal return in local currency, or almost exactly the rate of inflation. The worst returns occurred early in that sequence. With even a relatively low withdrawal rate, this investor would have run out of money within about a decade. Could the same thing happen to Americans who retire next year? I think it’s unlikely, but why take that unnecessary risk when owning a globally diversified portfolio should hedge against it.

CHAPTER 4 SUMMARY

Images   Standard deviation (SD) is a good measure of risk, but it’s far from perfect, since it doesn’t measure when those losses occur. During the worst of times, Treasury securities will protect your portfolio better than corporate or municipal bonds.

Images   While low correlations among asset classes are your friends, they are hard to find. Low-correlation stock and option assets are highly prized and thus see their prices bid up and have consequently low expected and realized returns.

Images   The bad news is that in increasingly globalized financial markets, short-term correlations among stock assets have risen. The good news is that over very long periods, global diversification should still prove valuable.

* (1.3 × 1.1 × 1.1 × 0.9)0.25 – 1 = 9.08%

CHAPTER 5

ASSET ALLOCATION FOR INVESTING ADULTS, PART 1

There Is No Asset Allocation Fairy

Adults don’t believe in children’s tales, and neither do informed investors.

By now, you know that there are almost no stock-picking fairies, star managers who will reliably beat the market. You might be lucky enough to latch on early to such a rare find, but you’re far more likely to come up with an expensive haystack than with the needle.

While we occasionally catch a fleeting glimpse of a stock-picking fairy, market-timing fairies simply do not exist. By sheer happenstance, one permabear or another will manage to precisely call a market crash. As we saw in Chapter 3, they invariably miss the spectacular market returns that follow.

In this chapter, you’ll learn that there is no asset-allocation fairy, neither a guru nor a quantitative technique that will magically find the asset allocation that delivers the highest future returns for a given amount of risk.

Let’s start our search for optimal portfolios with Figure 5.1, a simplified version of Figure 4.1 from the last chapter, which shows the returns and SDs of a mix of just two assets: the total US stock market and intermediate-term Treasuries.

FIGURE 5.1 Mixes of US total stock market and intermediate Treasuries, 1976–2021

Source data: Dimensional Fund Advisors and Bloomberg

This plot is essentially one-dimensional. Though it seems to curve through two-dimensional “mean variance space,” the investor can change only one variable: the stock/bond mix.

You could do a lot worse than the portfolios arrayed along this curve. Index funds in both asset classes can be bought from multiple vendors for a few hundredths of a percent per year in fees. Simply pick the point along the curve where you want to invest, that is, how much risk you want to take, and you’re done. The 50/50 mix, coined the “Couch Potato Portfolio” by financial journalist Scott Burns, has served many investors well over the decades.*

With three or more asset classes, the search for the optimal portfolio gets more complicated. A generation ago, to illustrate the process, I performed a relatively simple experiment. I had a math whiz friend generate 800 portfolios consisting of random mixes of one “safe” asset, the five-year Treasury, and six different risky stock asset classes:

Images   Five-year Treasuries

Images   S&P 500

Images   US small-cap stocks

Images   European stocks

Images   Japanese stocks

Images   Pacific Rim stocks

Images   Precious metals mining stocks (Morningstar fund average)

I rebalanced these random mixes each year during the five years between 1992 and 1996. The returns and SDs of these 800 portfolios plotted out as shown in Figure 5.2:

FIGURE 5.2 Mean-variance plot of 800 randomly generated portfolios

I never updated this study, because it turns out the actual years studied and assets chosen don’t matter. As long as you’re studying a period of several years and you mix together both risky and riskless assets, the plot will usually look something like Figure 5.2: a “porcupine” facing left with a relatively well-defined spine. That spine is the “efficient frontier,” which offers the most return for a given amount of risk, or looked at another way, the least amount of risk for a given return. (Over periods measured in decades, the plot flattens out and looks more like an anteater.)

Look at the vertical line, drawn at 15% of SD. This is approximately the risk level of the overall US stock market. Imagine yourself traveling up this line. If you can tolerate this high-risk level, you want as much return as you can get in exchange. You want to be as far up the line as possible.

Conversely, consider all the portfolios lying on the horizontal line, which correspond to the portfolios that return 10% per year. You want to be as far to the left of this line as possible and receive that 10% of return for the least amount of risk.

The holy grail of asset allocation is to locate the porcupine’s spine, the efficient frontier. In 1952, a young economics PhD named Harry Markowitz published a seminal article in The Journal of Finance that described a mathematical technique called mean variance optimization (MVO) for calculating the composition of portfolios lying on the efficient frontier. These went all the way from the “minimum variance” portfolio consisting of the riskless asset (in our case, five-year Treasuries) at the lower left to the “maximum return” portfolio at the top.¹

The inputs to Markowitz’s MVO algorithm, which involves moderately complex matrix algebra, consist of just three sets of parameters: the returns and the SDs for each of the several assets and the correlation matrix among them.

What could be easier? Simply collect the returns, SDs, and correlations for your asset classes and pour them into the magic black box—then out pop a range of optimal portfolios from minimum risk/return to maximum risk/return. Determine how much risk you want to take and then select the portfolio that delivers the maximum return at that risk level (SD).

I suggest a better way to design your portfolio: stuff half the money in your mattress and loan the other half to your ne’er-do-well nephew. MVO has two big problems. First, the “optimal portfolio” outputs are highly sensitive to their inputs, particularly asset return. Increase an asset’s return by a few percent, and it dominates the optimal portfolio mixes. Lower the return by a few percent, and that asset disappears from the optimal portfolio mixes. Second, because asset classes tend to mean revert, the optimizer is likely to overexpose the portfolio to assets that have had high prior returns and consequently will have low returns going forward. (Cynics sometimes refer to the mean variance optimizer as an “error maximizer.”)

How then to design your portfolio? Who better to ask than Dr. Markowitz himself:

I should have computed the historical co-variances of the asset classes and drawn an efficient frontier. Instead, I visualized my grief if the stock market went way up and I wasn’t in it—or if it went way down and I was completely in it. My intention was to minimize my future regret. So I split my contributions fifty-fifty between bonds and equities.²

There you have it. Dr. Markowitz considers the Shakespeare of investing—avoiding the hubris, fear, and historical accidents that ensnared Hamlet, Lady Macbeth, and King Lear—more important than its math, so he split the difference between stocks and bonds.

Speaking as the proud owner of the efficientfrontier.com domain, it really is too bad that there’s no asset allocation fairy who will reveal the efficient frontier portfolios of the next 5, 10, or 50 years. But you already knew that. The MVO algorithm favors the highest-performing asset classes. If you knew their identity in advance, you wouldn’t need the MVO in the first place.

THE TORAH OF ASSET ALLOCATION

Two millennia ago, a Gentile came to the two greatest living rabbis, rivals Shammai and Hillel, and asked the pair to teach the whole Torah while standing on one leg. Shammai, the Antonin Scalia of ancient rabbinical thought, angrily struck the man with a stick. The more tolerant Hillel then responded, “That which is hateful to you, do not unto another. This is the whole Torah. The rest is commentary; now go study.”³

For the individual investor, the financial whole Torah is the appropriate percentage of stocks and bonds in your portfolio. Once you’ve arrived at those numbers, the precise compositions of those two asset pools, which we’ll cover in later chapters, follow relatively easily.

CHAPTER 5 SUMMARY

Images   There is no asset allocation fairy, advisor, or black box that can tell you what asset allocation offers you the future highest returns for a given amount of risk.

Images   The most important part of investing is to determine how much risk is required to meet your goals and how much risk you can tolerate at each stage of your investing career. Make absolutely sure that the former isn’t larger than the latter.

Images   Once you’ve figured out how much risk you’re going to take during each stage of your life, precisely how to allocate your assets among particular classes of stocks and bonds becomes a more tractable task.

* Technically, the Couch Potato Portfolio is half each of the US total stock market and total bond market. The latter behaves very similarly to intermediate US Treasuries.

CHAPTER 6

ASSET ALLOCATION FOR INVESTING ADULTS, PART 2

The Ages of the Investor

At the risk of pushing the ancient literary allusions too far, I’ll add the riddle of the Sphinx to the Hillel parable:

What goes on four legs in the morning, two legs in the afternoon, and three legs in the evening? Man, who crawls as a baby, walks on two legs as an adult, and uses a walking stick in his twilight years.

The investor also has three ages, more prosaically, the beginning, middle, and end, each with its own theory and strategy. I’ll treat these out of order, leaving the middle age—the preretirement years—for last, since it is the trickiest.

WITHOUT A TRUST FUND, A YOUNG PERSON IS A GIANT BOND

A common joke among academics has a physicist approaching a hopelessly complex problem with “Consider a spherical cow.” The financial economist’s version of this canard is the classic Samuelson/Merton life-cycle theory. More than a half-century ago, Robert Merton and Paul Samuelson wrote a pair of mathematically dense papers that, translated into common English, concluded that if investors’ risk tolerances remained constant throughout their lives, then so too should their asset allocations remain the same.

This is a classic spherical cow assumption. Everyday experience shows that market behavior affects participants’ perceived risk tolerance, since even a few days or weeks of market panic dramatically lowers it. It’s even sillier to assert that risk tolerance doesn’t change throughout an investor’s life cycle.

Merton and one of Samuelson’s students, Zvi Bodie, along with Samuelson’s son William, improved on the Merton/Samuelson assumption of constant lifetime risk tolerance by extending it to include an investor’s human capital.¹

Consider a young person called Frida who has a secure job paying $50,000 per year. This gives her human capital—the present value of her future wages—well in excess of $1 million.

Frida’s liquid financial assets consist solely of $10,000 in a retirement fund with a 100% equity allocation. Since her human capital most resembles a bond that yields a relatively constant stream of inflation-adjusted income, her overall equity allocation is less than 1% of her aggregate human and investment capital. It makes no theoretical sense for her to own any bonds, because Frida’s bond-like human capital dwarfs her investment capital.

Taking this framework one step further, Frida’s equity exposure should be higher than 100%. That is, she should leverage the stocks in her IRA equities plan to the hilt, a strategy recommended by two other economists influenced by Samuelson, Ian Ayres and Barry Nalebuff. Their recommendation involves the purchase of “deep in the money” long-term equity anticipation securities (LEAPS) to achieve an approximate 200% equity exposure.* (Frida likely couldn’t accomplish this in her employer plan, but she might be able to in a brokerage IRA account.)²

There’s yet another theoretical reason why Frida should invest aggressively in stocks. Equities are less risky for young periodic savers than for older investors; consequently, anyone much under the age of 45 or so should devoutly wish for a crushing bear market so that she can acquire more stock shares at bargain prices.

Frida, unfortunately, is a flesh-and-blood human being, and not the financial economist’s spherical cow. Financial humorist Fred Schwed put it best nearly a century ago:

There are certain things that cannot be adequately explained to a virgin either by words or pictures. Nor can any description I might offer here even approximate what it feels like to lose a real chunk of money that you used to own.³

Young investors, who haven’t yet encountered serious equity losses, are especially vulnerable to market declines and the media hoopla that surrounds them. In the course of an ordinary and inevitable bear market, Frida will see an amount totaling a few months’ salary vanish from her plan’s quarterly statement, and she may well freak out. Much later in her investing career, she will almost certainly see dollar losses totaling years of salary.

The financial press makes a big deal about labeling a 10% fall in stock prices a “correction” and a 20% fall a “bear market.” Such definitions constitute mindless numerology. Stock prices behave the same way after they’ve fallen by 20.1% or 19.9%. But these distinctions do say a lot about how seriously investors take the inevitable 10% and 20% price falls, which occur (respectively) an average of once a year and once every five years. In fact, three or four times during the past century (depending on how one counts), stock prices declined by roughly half. On one occasion between 1929 and 1932, they declined by almost 90%.

In this context, it’s worth remembering Senator Burr’s famous “get all our money out of the bank” phone call to his wife in the fall of 2008, when stocks had declined by only about a quarter. Stocks don’t fall that much without a highly compelling underlying narrative, usually involving a financial system panic or a geopolitical catastrophe; such market ructions seem to occur about once per decade. Most financial advisors, if they’ve been around long enough, will encounter a military veteran or two who faced death in combat with equanimity but who threw up when their portfolios lost 5%. Two hundred percent market exposure? In a humorous exchange at a Boston University conference, even Samuelson repudiated the Nalebuff/Ayres leveraged strategy for young investors.⁴

The reasons we’re averse to financial risk are likely evolutionary. In the calorie-poor environment of our Stone Age past, even slight resource shortfalls or minor exposures to predators, poisonous foods, or hostile tribes could prove fatal. It was better not to take too many chances. Manifestly, Mother Nature did not design human beings with equity risk in mind.

In order to better determine Frida’s real-world risk tolerance, I advise her to start low and go slow. This generally takes a market cycle or two, so she would do well to go easy on stock exposure during the first several years of her investment career. Her aim should not be to get rich, but rather to not die poor, and one of the surest paths to penury in old age is to swear off stocks at a young age because of a significant nest-egg loss. If she’s one of the rare young people who can tolerate a stock-heavy portfolio, all the better. She’ll still have plenty of time to increase her equity exposure and reap the benefits of a high-risk tolerance.

MATH BOX

Risk Aversion

The average investor is most constrained by risk tolerance. A classic study by economist Robert B. Barsky and his colleagues asked subjects the following question:

Suppose that you are the only income earner in the family, and you have a good job guaranteed to give you your current (family) income every year for life. You are given the opportunity to take a new and equally good job, with a 50–50 chance that it will double your (family) income and a 50–50 chance that it will cut your (family) income by a third. Would you take the new job?⁵

This sort of question yields the so-called relative risk aversion (RRA) factor, which roughly translates to how frightened you are of risk. For example, if you answered “yes” to the preceding question, your RRA was less than 2. If you answered “no,” it was more than 2; if you answered “not sure,” it was close to 2. One calculates RRA as [(1 − x)/x], where x is the one-third loss, that is, [(1 − 0.333)/0.333] = 2. If you were at equipoise with only a 10% loss of salary, your RRA zooms up to 9 [(1 – 0.1)/0.1]. On the other hand, if you’re willing to suffer a 50% chance of a 100% loss of salary, your RRA is zero. (The RRA makes sense only so long as the bet’s expected return is positive.)

Barsky and his colleagues found that for most people, the RRA measured from sequential questions of this sort was quite high. Nearly two-thirds of the respondents would not accept even a 50/50 chance of a 20% loss of income, which means that their RRA was greater than 4 [(1 – 0.2)/0.2]. They also found that the RRA correlated not only with the percent of equity held by respondents, as might be expected, but also with other risk-taking behavior: those who smoked, drank, and went without insurance had, on average, lower RRAs.⁶

Mind you, these data refer exclusively to how much risk people say they can tolerate, a good analogy being the difference between practicing an aircraft crash in a flight simulator and the real thing. The responses to this sort of questionnaire, most commonly administered to study populations of undergraduates at elite colleges, may have little bearing on how a middle-aged person actually behaves when she sees half her nest egg vanish.

THE MOST IMPORTANT NUMBER FOR RETIREES

Let’s shift our focus to the retirement phase of life. We’ll start with a 65-year-old retiree named Fritz who has a $750,000 portfolio, $50,000 in annual living expenses, and Social Security and pension checks totaling $20,000 per year.

Fritz thus needs to come up with $30,000 more each year to put food on the table, pay his rent or mortgage, cover Medicare premiums, take his wife to dinner, and visit the grandkids. Call this additional annual $30,000 his residual living expenses (RLE).

The primary goal of retirement savings is to cover basic living expenses over the rest of the investor’s lifetime. Ideally, this should include at least 25 years of RLE. Fritz barely has these extra funds, as 25 years times $30,000 exactly equals his $750,000 nest egg. With these figures in mind, he can’t afford much risk. Every 4% loss in his portfolio theoretically makes him destitute for one year of his approximate life expectancy. He cannot afford to lose any of his nest egg in stocks, so his portfolio should be heavily invested in low-risk assets whose payoff profile matches his after-inflation retirement needs. The key word in the preceding sentence is “matches,” ideally an inflation-adjusted annuity that supplies his RLE each year.

By far, the best way to do this, unless both Fritz and his spouse have short life expectancies, is to “buy” the inflation-adjusted annuity offered by Social Security deferral to age 70 by spending down retirement savings until that age. Ideally, he should buy an inflation-adjusted annuity to make up the difference. Unfortunately, insurance companies stopped offering those a few years ago.

The next best option is a TIPS ladder. Since TIPS provide a riskless inflation-adjusted payoff at maturity, theoretically Fritz should own bonds maturing each year of his retirement. In the real world, this isn’t possible for two reasons: first, because as of 2023, there are no TIPS maturing between 2034 and 2039, and second, because the longest TIPS maturity is 30 years, and if Fritz or his spouse live beyond age 95, the ladder falls short. A commercial annuity theoretically offers Fritz income beyond age 95, which I’m wary of for reasons that I’ll come to shortly.⁷

In reality, Fritz has no need to take risk, since he has already acquired precisely enough assets to retire. His risk tolerance is irrelevant, since his capacity and need for risk already control his asset allocation.

But shouldn’t a mixed portfolio of stocks and bonds see him through any circumstance? No. Consider that for nearly two decades from the late 1960s to the early 1980s, both stocks and bonds had negative real returns. By the time the cavalry arrived in 1982, his portfolio would have been nearly gone. Further, stock valuations are higher and thus their expected returns are lower than they were in the mid-1960s.

In the past, portfolios containing between a 25/75 and 75/25 stock/bond ratio did indeed sustain burn rates in excess of 4%. The most widely quoted examination of burn rates, the Trinity Study, demonstrated that spending an inflation-adjusted 5% of the initial value of a 50/50 stock/bond portfolio had a 76% probability of success, defined as dying without debt after 30 years of retirement. More commonly, the so-called Bengen rule, named after financial advisor William Bengen, posits the safety of an annual withdrawal rate of 4%.⁸

The problem with both the Trinity Study and the Bengen rule is that they rest on historical returns, which were likely much higher than those currently on offer. The Trinity authors and Bengen used historical data from 1926 to the mid-1990s, which blessed investors with real stock returns of 7% and real bond returns of 2%. The reason for those high stock returns was the dramatic increase in stock valuations over that period, which is unlikely to repeat. Future stock returns are likely to be lower, which means that even the Bengen/Trinity 4%–5% withdrawal rates may be optimistic. When I wrote the first drafts of this edition, real bond yields, expressed by the TIPS interest rate, were negative, a problem “solved” by the 2022 bond bloodbath. As of this book’s writing, bonds are yielding close to their 2% historical real yield, but this is likely the result of temporary monetary tightening by the Federal Reserve, and even after the 2022 debacle, stocks are not likely to provide anywhere near the 7% real return of the post-1926 period studied by Bengen/Trinity.

Since the relationship between burn rate and portfolio survival is such an important subject, I’m going to start with the high raw historical returns Bengen/Trinity used. The graph in Figure 6.1 plots what happened at a 4% burn rate: $40,000 annual real withdrawals from an initial $1 million 50/50 portfolio of half S&P 500 stocks and 5-year Treasury notes, for someone retiring in 1926, 1936, 1946, 1956, 1966, 1976, 1986, and 1996.

FIGURE 6.1 Portfolio drawdowns at a real 4% burn rate of 50/50 stock/Treasury note mix from various retirement years. The y-axis is shown in inflation-adjusted dollars.

Source data: Dimensional Fund Advisors

Figure 6.1, which is plotted out in inflation-adjusted dollars, is entirely consistent with the Trinity Study and Bengen rule. Four percent withdrawals of inflation-adjusted dollars were reasonably safe. I chose years ending in “6” for two reasons: first, because the database begins in 1926, and also because 1966 was the worst possible time to begin retirement, with the nest egg barely surviving 30 years. Financial economists call the possibility of picking a disadvantageous year to retire “sequence-of-return risk,” and it’s nothing to sneeze at, as Figure 6.1 shows.

Over the next several decades, stocks will likely not provide a 7% real return, and bonds likewise may not provide a 2% real return. What’s reasonable? I repeated the exercise in Figure 6.2 by adjusting the monthly stock series down to produce a 4.5% real return between 1926 and 2021, and did the same to the 5-year Treasury series to produce a 1.0% real return.

FIGURE 6.2 Portfolio drawdowns at a 4% real burn rate of 50/50 stock/Treasury note mix from various retirement years. The y-axis is plotted in real dollars.

Source data: Dimensional Fund Advisors

Here’s what falls out of that exercise.

At these expected returns, three of the eight starting dates failed to make it to 30 years, the one beginning in 1966 disastrously so. Only when the withdrawal rate is lowered to 3.17% do all eight portfolios clear the 30-year bar. (Technically, the 1996 starting date hasn’t reached 30 years, but it performs well enough at 26 years that its 30-year survival seems assured.)

This exercise confirms the suspicion of many retirement authorities that “3% is the new 4%” for those approaching retirement. If your burn rate is much above 3.5%, you’re in the red zone. Unless you’re single and in poor health, or both you and your spouse are in poor health, your first priority is to draw down your retirement assets in order to defer your Social Security payments to age 70, which is the best annuity that money can buy. Whatever’s left over should be invested conservatively with an eye toward inflation protection, particularly a TIPS ladder with maturities that match your outflows. Many retirement experts also recommend an immediate fixed annuity, which I’d consider with the following caveats. First, annuities carry the credit risk of the issuing insurance firm. While it’s true that these generally have state government backing, a severe financial crisis will cut through a state’s insurance reserves, which are funded by other insurance companies, like a hot knife through butter. (In 2008, the US government rescued AIG, which sold annuities. Since then, the US debt/GDP ratio has soared past 100%, and it’s questionable whether Uncle Sam would be able to save annuitants’ bacon again.) If you do buy an annuity, it’s best to spread your purchases among two or three different issuers. Second, no annuities with true inflation protection are available, only a fixed payment escalator that will prove inadequate with severe inflation and will offer a lower initial payout than one without an escalator. Finally, it cannot be said often enough: you shouldn’t purchase a TIPS ladder or a fixed annuity until you’ve first “paid” to delay Social Security to age 70.

If your burn rate is between 2% and 3.5%, you’re probably in good financial shape. You should still defer Social Security to age 70 and have a reasonable stock/bond mix (between 25/75 and 75/25), which should service your retirement needs fairly well.

Finally, if your burn rate is less than 2%, your retirement asset allocation doesn’t matter to you as much as it matters to your heirs and charities. This is especially true if you’re one of the lucky and frugal few with Social Security and pension income sufficient to meet your living expenses. Beyond splashing out for a beamer or the occasional business-class seat, your portfolio returns are irrelevant to your material circumstances.

MATH BOX

Monte Carlo Analysis

The problem with using past equity performance is that historical market returns can be a cruel, misleading mistress. In the United States, we have only about a century of high-quality data; the United Kingdom and the Netherlands have only a few more centuries of fragmentary numbers on a few stocks. As we’ll see in the next chapter, while there are millennia of data on loan investments, their relevance to current markets is nil.

One way to approach the problem of limited historical data is Monte Carlo analysis, which generates random return sequences around a given mean and SD, most often using monthly returns. For example, one commercial product, MCRetire®, will produce within seconds a million iterations of any given portfolio. Consider one, for example, with a 2.5% real return and an SD of 8%, which approximates the expected future behavior of a 50/50 portfolio. At a 4% burn rate, its portfolio survival was 100%, 98.9%, 75.5%, 45.7%, and 28.4% at 10, 20, 30, 40, and 50 years.

The serious investor can find Monte Carlo tools online. One of the most widely used is https://www.portfoliovisualizer.com/monte-carlo-simulation. Its complex input options make using it tricky. For example, to input return/SD for an overall portfolio, select “simulation model, parameterized returns.”

Monte Carlo analysis lets you see how your burn rate, portfolio returns, and portfolio SD impact your nest egg’s survival. Its disadvantages are many. First and foremost, it assumes random-walk behavior, which does not allow for the slight tendency toward long-term mean reversion in stock returns. You can compensate for this by slightly reducing the SD assumption. More importantly, Monte Carlo imparts a false sense of precision reminiscent of the following joke: How do you know that financial economists have a sense of humor? Because they use decimal points. Retirement planning, and financial analysis in general, is not an airfoil or electrical circuit with exquisitely predictable behavior; although Monte Carlo does a decent job of simulating the random nature of security returns, it largely ignores the lumpy fat-tailed personal events that can explode living expenses, particularly costly medical surprises and especially long-term care, for which insurance solutions are either inadequate or prohibitively expensive.

Still, for those with a quantitative bent, Monte Carlo provides a useful way of internalizing a stochastic approach to financial planning.

AN ALTERNATIVE WAY TO LOOK AT RETIREMENT INCOME: THE LIABILITY MATCHING PORTFOLIO AND THE RISK PORTFOLIO

The aim of retirement saving and investing is not to get rich, but rather to minimize the risk of becoming poor. The very best way to do that is to, in finance-speak, “defease your liabilities,” that is, to precisely offset your inflation-adjusted living expenses on a year-by-year basis.

Deferring Social Security to age 70 accomplishes this best, since its benefits are inflation adjusted. For most retirees, though, deferring benefits to age 70 proves inadequate. The most precise and secure way of closing the gap between Social Security and your living expenses is with a TIPS ladder whose rungs mature as you age, but this approach still has drawbacks. First and foremost, TIPS yields have varied widely over the past few decades and have often strayed into negative territory in the past several years. Second, as previously noted, there are currently no TIPS maturing between 2033 and 2039, although this gap will slowly close by 2029 with successive auctions of the 10-year securities.

Last, TIPS taxation is messy, so they’re best held in IRA accounts. (I bonds, which are available from Treasury Direct or from the IRS as payment of a tax refund, are cleaner in this regard, since they defer taxes on their appreciation to sale. Their purchase is limited to $10,000 per year per person, plus up to $5,000 in a tax refund.) If TIPS yields fall well below zero, as was true for much of the time between the 2008 financial crisis and early 2022, the best bet likely is to cross your fingers, sock away your money in short Treasuries, and pray for future higher yields.

How big should your “liability matching portfolio” (LMP) be? Fritz, for example, needs 25 years of RLE; this corresponds to a 4% burn rate (1/25 = 4%). Why shouldn’t Fritz invest his retirement nest egg in a mixed stock/bond portfolio? Figure 6.2 provides the answer. If you encounter its retire-in-1966 scenario—“sequence-of-return risk,” in finance-speak—your portfolio may not survive for even two decades. The good news is that once you’ve accumulated an LMP of safe assets, you’re free to invest additional money in a “risk portfolio” (RP) that will benefit your heirs and charities.

In truth, the LMP/RP construct is simply another way of describing a “two bucket” approach that mentally compartmentalizes your bond and stock holdings. It’s a psychological hack that deals with the bad hand Mother Nature deals to humans for handling long-term financial risk. As that great investment strategist, Yogi Berra, said, “Ninety percent of the game is half mental.”⁹ Two mental buckets make it easier to stay the course during the rough times when, with apologies to John Lennon, happiness is a warm bond.

AGE IN BONDS?

A hallowed prescription for asset allocation dictates that your bond allocation should be your age and that your stock allocation should be 100 minus your age; that is, you should lower your stock allocation by 1% each year. A 20-year-old thus holds an 80/20 stock/bond allocation, which gradually decreases to 35/65 when she retires at age 65.

This is not a bad strategy, but may not be appropriate for someone like Fritz, who has exactly 25 years of RLE saved up and whose retirement could get fried with bad initial returns in stocks and bonds, as happened after 1966.

Now let’s conjure up Fritz’s more fortunate cousin Frank, who also needs a $750,000 LMP (25 years times $30,000/year), but has a $3 million portfolio. If he’s handled severe stock market declines with equanimity, and if he wants to endow his heirs and charities, there’s no reason why he couldn’t invest his RP, the $2.25 million he doesn’t need to retire, in stocks. He now owns a 75/25 portfolio.

Further imagine that Frank still has $3 million at age 90. Even if he and his spouse live to 105, he now needs only a $450,000 LMP, and an 85/15 portfolio is probably safe. In fact, even an all-stock portfolio that yields well in excess of $30,000 per year in dividends would likely be bulletproof. Frank’s burn rate, after all, is just 1% per year ($30,000/$3,000,000). If Frank spends down his LMP and doesn’t touch his RP, the longer he survives into old age, the higher his equity allocation becomes. This logic is encapsulated in a well-regarded paper by Wade Pfau and Michael Kitces that recommends a “reverse glide slope” strategy that involves slowly increasing equity allocation after retirement.

A close examination of their data, though, shows that a reverse glide slope only slightly increases the odds of success over the standard age-in-bonds method.¹⁰ In any case, a reverse glide slope in retirement makes sense. The new retiree needs a large LMP, but the required size decreases as they get ever closer to pushing up the daisies.

This introduces the final retirement risk: living too long. Suppose, for example, you retire at age 60 with a 25-year LMP. What happens if you or your spouse makes it past 85?

Once again, deferring Social Security to age 70 is the best way to avoid an Alpo diet in old age. Beyond that, insurance companies offer deferred annuities, which can start payouts as late as age 85. They’re a bad idea for several reasons. First and foremost, they don’t come with an effective inflation rider. If you purchase a deferred annuity at age 60 that begins its payout at age 80, you’re taking 20 years of inflation risk. During the two decades between 1966 and 1985, the purchasing power of the dollar declined to $0.29, not something you’d like to happen to the longevity insurance you thought would be there for you past age 85.

Even worse is the credit risk you shoulder by handing your hard-earned money to an insurance company for decades before getting a penny back. Financial history teaches that a lot can happen in 20 or 30 years, even to the survival of whatever state guarantee sits behind your policy.

A preferable solution to this “longevity risk” might be to lock perhaps 10% of your stock assets into a mental account. Although equities can be risky even over such long horizons, economic history suggests that this long-term equity risk poses a lesser threat to the retiree than does the inflation risk of a nominal-dollar payout from a deferred annuity insurance product. You might soften the equity risk of this homegrown longevity insurance by deploying its dividend stream into sequential 30-year TIPS auctions, or opportunistically exchange some of the equity at high prices for 30-year TIPS along the way. Admittedly, only a minority of retirees will likely be amenable to such an unorthodox approach.

Finally, if you can defer the purchase of a TIPS ladder to age 70, you’ve effectively solved the longevity problem with the purchase of a good dollop of the 30-year bond.

THE MIDDLE (PRERETIREMENT) YEARS: THE TRICKIEST GAME OF ALL

I’ve saved the middle age of the investor—roughly the decade before retirement—for last because it’s the most difficult and uncertain phase in the investing life cycle. It marks the transition between the aggressive investment strategy of the early years and the potentially conservative investment strategy later on.

Early in your investing lifetime, the focus is on rapidly building up assets. A rich wage stream and future human capital mitigates the risks of stock ownership, but later in life, when an investor’s human capital is depleted, the sequence-of-return risk served up by both equities and bonds leaves little margin for error.

When and how do you transition from a risky young-investor strategy to a low-risk retiree strategy? One perfectly acceptable way formulaically reduces your equity allocation as a function of age. Maybe by age 40 you know you’re comfortable with a 70/30 stock and bond mix. You might decide that by age 70, you want to be no more than 25/75.

This entails lowering your equity allocation by 1.5% each year between ages 40 and 70. Yet another way would involve a gradual switch from a bond fund to a TIPS ladder, as detailed by Michael Zwecher in his book Retirement Portfolios.¹¹

Markets fluctuate unpredictably and may not cooperate with these strategies, so I suggest another path. If at any point during the decade before retirement a bull market pushes your portfolio over the LMP “magic number” of 20 to 25 times your residual living expenses, you’ve won the investing game. Why keep playing it aggressively? Start bailing out of stocks. Once you’ve put enough TIPS, plain vanilla Treasuries, and CDs into your mental LMP, you’re free to again add stocks to your risk portfolio.

The uncertainty surrounding exactly when or even if you’ll need to shift from the early strategy to the late strategy is daunting, since the timing depends on many different things: your savings rate (more equals sooner, less equals later), the equity returns series (poor-returns-early means sooner, good-returns-early means later), and the overall magnitude of the returns. Some fortunate folks will fill their LMPs while still reasonably young. Others who use the same strategy but begin a few years later may never do so.

If your burn rate looks like it will be in excess of 3.5%, allocate enough relatively safe assets to pay for an LMP of at least 20 years of RLE—the gap between Social Security/pensions and living expenses. And even if you’re tired of hearing me repeat this, under most circumstances, you should spend down the LMP to benefit from the superb longevity insurance provided by deferring Social Security until age 70.

On the other hand, if your projected burn rate is 2% or less, even an equity-heavy portfolio will survive all but the most dire market conditions, in which case most, if not all, of your residual living expenses will be covered by the dividend return on your equities—again, assuming you have the risk tolerance to handle a near 100% equity portfolio.

IT’S ALL IN THE TIMING

Those who began their working careers and saved during the worst of times—the decades of the 1930s and 1970s—paradoxically did the best, because they were able to accumulate equities at low prices. This assumes that they actually had steady work in those tough times—no small thing—and further had money to spare for savings. On the other hand, those who began working in the boon times of the 1950s and 1960s took much longer to accumulate adequate nest eggs.

As a thought experiment, I posited imaginary annual cohorts that invested 20% of annual salary in the inflation-adjusted S&P 500 at the end of each year. I then measured how long each of these cohorts took to reach a portfolio size of 20 years of salary, starting with the cohort that began work in January 1925 and began investing a year later. (That portfolio size constitutes a 25-year LMP, since presumably the cohorts were able to live on 80% of their salaries.) Figure 6.3 shows how long it took each cohort beginning work from 1925 to 1993 to reach that retirement goal.

FIGURE 6.3 Years to acquire LMP by year starting work (see text)

Source data: Dimensional Fund Advisors

While the cohort that began work in 1980 took just 19 years to reach the 20-years-salary finish line, the one that began work in 1949 took 37 years. This makes sense. Recall the savings accumulations of Mr. Forward and Mr. Reverse from Chapter 1. It’s far better to experience poor returns at the beginning of the savings path. Cohorts starting work in the decade after 1945 did so at the beginning of one of the most powerful, prolonged bull markets in the history of US equity returns and took longer to reach the 20-years’ salary LMP. Those who began work after about 1970, on the other hand, did so at the onset of a prolonged bear market and reached it sooner.

Note the “waterfall” phenomenon in Figure 6.3. Successive cohorts took progressively less time to reach the goal as the time to the next bull-market peak shortened, until the next cohort just missed achieving the 20-year salary LMP at that peak and wound up taking much longer. You can see the first waterfall with the 1943–1945 cohorts, which just missed being able to retire with the mid-1960s market peak and had to wait another decade and a half for the markets to recover. The second waterfall occurred with the break between the 1980 and 1981 cohorts. The former achieved the 20-year salary LMP goal in just 19 years, while the 1981 cohort, having just missed the mark in 1999, got ambushed by both the 2000–2002 and 2007–2009 bear markets before finally making the grade in 2013. As of the end of 2021, the 1994 cohort came up just short after toiling away for 28 years, then got whacked by the 2022 bear market; later cohorts are even farther behind.

The experiment shown in Figure 6.3 is a bit of a statistical cartoon that contains many strong (and probably offsetting) assumptions, including the absence of Social Security benefits and the 100% investment in stocks, but it still illustrates a valid point. You just don’t know when you’re going to achieve your LMP, and when you do, it’s best to act.

This cohort variability not only carries momentous personal freight for the individual investor, it also has enormous implications for public policy. It’s becoming increasingly clear that the headlong rush into defined-contribution retirement schemes will not turn out well. At some point our whole system of retirement saving will need a major overhaul. Whatever new system emerges, and no matter how it is designed, some demographic cohorts will do better than others. Such is the nature of uncertainty in the capital markets, for the individual and for society alike.

This is an ugly reality that gets almost no attention. Anyone who saves to retire of necessity plays demographic roulette. As we’ve seen, the markets may be paradoxically kind to those who find jobs and begin their working careers during periods of distress, such as the grim years of the 1930s and 1970s, while those who began work in boon times, such as in the late 1990s, will not do as well. A short work career—think a fellowship-trained surgical subspecialist who does not begin a career until age 35—will magnify the chances of a poor demographic draw.

As we tell our children, life is not fair. The gods can reward the lucky but somewhat imprudent investor with a favorable draw of early low returns, later high returns, and a conversion to safer assets just before a market peak. The prudent but unlucky investor may do everything right and still never accumulate an adequate LMP, continuing to work through retirement and enduring an underfunded, insecure old age. But by saving like mad and playing the life-cycle game as well as you can, you stack the odds in your favor.

CHAPTER 6 SUMMARY

Images   Because their human capital dwarfs their investment capital, young people in theory cannot invest aggressively enough. But even if they can talk the equity talk, they may not be able to walk the equity walk. Better to figure that out early by starting at a relatively low equity allocation.

Images   The retiree, by contrast, has had time to become familiar with their ability to handle investment risk, but their burn rate may be high enough to fall afoul of sequence-of-return risk. On the other hand, if their burn rate is low enough, their actual stock/bond mix may not matter all that much, since most of their nest egg belongs to future beneficiaries.

Images   The transition from young saver to retiree, which occurs roughly in the decade or so prior to retirement, is the trickiest of all. If at any point during the decade before retirement you’ve accumulated enough to safely meet your basic living expenses, start taking some risk off the table. Better to fly coach and buy your clothes at Target because you invested too conservatively than to wind up involuntarily living with your kids because you invested too aggressively.

* A “deep in the money” call option is one whose strike price is well below the actual market price.

CHAPTER 7

ASSET ALLOCATION FOR INVESTING ADULTS, PART 3

Model Portfolios

Having discussed the investing version of Hillel’s whole Torah—the stock/bond allocation throughout the investor’s life cycle—in the last chapter, this one will cover the commentary, which for investors comprises two main questions:

Images   What stock categories should you buy? What is the appropriate allocation to foreign stocks? Should you tilt your portfolio to small stocks and value stocks? Do ancillary asset classes such as REITs, energy stocks, and precious metals equity have a place in your portfolio?

Images   What bonds should you own?

Having considered these two issues, I’ll discuss the range of possible model portfolios they imply.

BROAD STOCK ASSET CLASSES

I’ll start with the total world stock market as mirrored by the FTSE Global All Cap Index, which is currently split about 61%/39% between US and foreign equities.

For the US investor, this isn’t a bad allocation, but you might want a different foreign exposure. If you’re like most people, your retirement liabilities will be in dollars, so a 39% foreign allocation might seem inappropriately high. Remember: your bonds will be held almost entirely in dollars.

Foreign stocks are not only slightly more difficult and expensive to trade but are also subject to foreign tax withholding. This presents no problem in taxable accounts, since those taxes will offset your liability to the IRS, but you lose that deduction if you hold foreign stocks in a sheltered account. This doesn’t mean that you shouldn’t own them at all in a sheltered account. It’s merely a thumb on the domestic side of the scale.

On the other hand, foreign stocks are currently selling at lower valuations than US stocks and have higher expected returns. Accordingly, a foreign stock allocation between 30% and 50% seems reasonable. If you like simplicity, a single, all-world stock index fund provides excellent one-stop shopping. If that’s too simple for you, or if you’d like to have more granular allocation control, adjust that with appropriate holdings of total US and total international stock funds.

We can further break down the international allocation along geographic lines:

Images   Into two funds, one for developed foreign markets (the United Kingdom, France, Germany, Japan, Singapore, etc.) and one for emerging markets (Latin America, Eastern Europe, Thailand, Indonesia, etc.)

Images   Into three funds: European developed markets, Pacific developed markets, and emerging markets

HOW MUCH TILT? WHAT KIND OF TILT?

The first question is whether tilting toward small and value stocks still offers a return premium. The answer is probably yes. The premium for value stocks is a classic example of Ilmanen risk, that is, bad returns in bad times. Ilmanen risk certainly showed up in the two great panics of the past century, in 1929–1932 and 2007–2009, when value stocks lost even more money than the broad market.

Theoretically, the young saver should tilt her portfolio toward small value stocks, but the small and value premiums are quite fickle. The last several decades have not been kind to either factor; the value factor has yielded negative returns for more than the past 25 years. Small company stocks are even more fickle, underperforming large-cap stocks for the past 40 years!

This long-lasting underperformance of both the small and value factors, though, is of more concern to lump-sum investments than to a stream of periodic investments, because the ability to occasionally purchase small and value stocks at a low price mitigates temporary underperformance. In my booklet The Ages of the Investor, I found that because of their higher volatility, even during periods when small value stocks slightly underperformed the S&P 500, dollar cost averaging into small value stocks came out ahead of a more conventional S&P 500–based strategy most of the time.*

At the end of the day, a tilt toward small and value stocks is a bet on risk premiums; that is, on risks that have shown up with a vengeance in past decades. On the other hand, value stocks are currently trading at a deeper than usual discount relative to growth stocks, which suggests that investors may be rewarded for a value tilt in the future.

Just as your equity exposure depends on how well you can tolerate stock price falls, how much to tilt to small and value stocks depends upon how well you deal with underperforming the broad market, both temporarily and permanently. If your tolerance for underperforming the market is low, I’d stick with foreign and domestic total stock market funds, which both have a modest exposure to mid-cap and small-cap stocks.

But if you’re young and can tolerate underperforming the broad stock market for long periods, then multiple fund families currently offer low-expense, small value funds that can be added to your asset allocation mix. An aggressive young investor, for example, might hold two-thirds of her stock exposure in total stock market funds and a third in small value funds.

ANCILLARY STOCK ASSET CLASSES

I suspect that if you’re reading this book, you’re looking for something a bit more detailed. A small allocation to REITs might be worthwhile, taking into consideration whether or not the US and international stock index funds in your portfolio already own them. For example, Vanguard’s index funds include REITs, while the broadly diversified funds offered by Dimensional Fund Advisors and Avantis don’t. Last, a smidge of precious metals and natural resource stocks, beyond those already held in your main foreign and domestic fund holdings, can provide a bulwark against inflation and geopolitical instability, as they did for 2017 to 2022. Financial history shows that inflation is the most salient macroeconomic risk facing the investor in a fiat (paper) money world, which usually benefits commodities producers during periods of rapidly rising commodity prices.

HAPPINESS IS A WARM BOND

Bonds are easier. They’re your lifeboat, your sleeping draught, and your option on the future. As we saw in Figure 1.8, corporate bonds can take a real haircut (as can longer munis) when you need them to pay your living expenses and to purchase stocks at depressed prices. During the last few severe bear markets, longer Treasuries did very well, but beware. When interest rate increases drive down stock prices, duration can be a real killer, as happened in 2022, when long Treasuries lost 30% versus “only” 18% for the S&P 500. Stick to short Treasuries, CDs, and munis. If it’s not too much trouble, own your Treasuries individually in a 3- or 5-year ladder, which is the furthest out I’d go. If that is too complicated, a low-cost short-term Treasury or government bond fund is a good substitute.

Because of price opacity, spreads, and the need for wide diversification in the municipal bond market, by far the best choices are the various Vanguard municipal bond funds, going out no further than their “intermediate” national and state-level funds. One word of warning about state-specific funds: although it’s tempting to avoid state income tax with these, I’d make such a fund no more than half of your muni holdings because of the systematic risk of state-level fiscal problems.

Except in extraordinary circumstances, corporate bonds don’t make a lot of sense. Besides their stocklike behavior in a panic, there’s also a good theoretical reason not to hold them: the agency conflict between a company’s bond and stockholders. Bondholders have no upside beyond par at maturity, so they care only about the safety of interest and principal coverage. Stockholders care at least as much about the potentially unlimited upside of equity, so they’re willing to seek out risk to get that upside. The problem is that stockholders get to vote, not the bondholders.

If stock prices fall by half or more, you’ll have to sell a fair amount of fixed-income instruments to make stock purchases. As a severe, prolonged market downturn progresses, you’ll likely buy equities at progressively lower prices. By the summer of 2008, most disciplined investors were already adding to their equities at what seemed like depressed prices; then came the Lehman failure in mid-September, followed by even further declines and purchases in October and again in November, before the markets eventually bottomed in early March 2009. How will you feel about repeatedly spending your precious liquid reserves (short-term Treasuries, CDs, and money market funds) during such a downturn, after you’ve already plowed a fair amount of them into risky equities? More important, how much of your investing discipline will survive a real market panic? You won’t know the answers to those questions until this actually happens, but if your “cash” is not of the highest quality, your discipline, and the magic of compounding along with it, will likely not survive.

SOME MODEL PORTFOLIOS

Portfolio design and meal planning have a lot in common. Some people eat to live. They don’t fixate on calories and they don’t devote a lot of thought or effort to cooking or restaurant choice. They have better things to do with their lives.

Others live to eat. Not only do they obsess over the quality of their cooking ingredients, culinary technique, or whether to go out tonight for north Italian or south Indian, but their cooking and eating habits can even define their very identity.

Personal finance is like that too. Are you a basic meat-and-potatoes investor who has higher priorities than the complexity of your retirement portfolio, which you view as a matter of necessity and nothing more? Or are you a portfolio gourmet who obsesses over every last percent allocated to each asset class?

Although I believe that the latter group may benefit from higher long-term risk-adjusted returns, the last two decades, with their relative outperformance of total market funds, have offered a cautionary tale about the benefits of a simple meat-and-potatoes portfolio over more exotic ones.

A perfectly serviceable asset allocation strategy can run the gamut from a single target date fund, which is increasingly the default option in many employer-based defined contribution plans, to more than a dozen assorted domestic and foreign stock funds with different geographic and factor tilts, in addition to the bond allocation.

Some people seek simplicity; others revel in complexity. Which approach turns out to be superior in the end pales in importance to the survival of your asset allocation, which in turn depends on your ability to stay the course under pressure.

One and Done

Over the past few decades, retirement plan sponsors have increasingly made target-date funds the default choice for their participants, and the largest provider of these funds is Vanguard. I’ve listed their target-date funds and their allocations. For the sake of compactness, I’ve listed the target date for retirement, the purchaser’s implied age at this book’s 2023 publication date, ticker, expense ratio, and asset allocations. For example, the full name of the 2065 fund is the Vanguard Target Retirement 2065 Fund, ticker VLXVX. If we assume that it’s aimed at someone who wants to retire in that year at age 65, then the participant is 23 years old in 2023. (That is, [target date] – [retirement age] = [birth year].)

These funds come with multiple caveats that result from their implied “one size fits all” construction. First, this series follows the conventional mandate for very high stock allocation early in the worker’s career and is far more aggressive than the traditional “age in bonds” strategy. The funds at the top of the list hold about 89% stock all the way to age 43, following which the stock allocation glides down by about 1.6% per year. This allocation may grossly exceed many investors’ risk tolerance and cause them to violate Charlie Munger’s prime directive of compounding: never interrupt it. A suboptimal allocation you can execute is better than an optimal one you can’t.

Second, the “one size fits all” design also ignores retirees’ differing burn rates. At one extreme, a 42% stock exposure for the new retiree—the allocation of the 2020 fund for today’s 68-year-old—may be simply too high for someone who is spending more than 4% of their nest egg annually. A bad initial returns sequence on top of already low expected real stock and bond returns may well wipe out that investor within 20 years. The optimal strategy for anyone in that unfortunate position is to draw down retirement assets, defer Social Security to age 70, and invest the rest in a TIPS ladder, or at least to have a much more conservative stock/bond mix.

Third, the total bond market component of these funds contains about 30% corporate bonds, the drawbacks of which were covered in Chapter 1. In addition, the duration of the domestic and foreign “total bond market” components of these funds is a bit too long for comfort at around seven years. As investors found out in 2022, in an inflationary environment, this will drag down performance just when they can afford it least: Ilmanen’s “bad returns in bad times,” the most dangerous flavor of risk.

Finally, the fund family’s strategy may go off the rails. As I wrote this chapter, Vanguard announced that it’s planning to slowly add private equity investments to its target date lineup, while other providers were looking at cryptocurrency and commodities exposure. Mutual fund companies don’t have an impressive track record with these sorts of strategy adjustments, often arriving late at the asset allocation banquet table and winding up with the tuna noodle casserole.

Still, these funds serve a useful purpose. Even if their strategies are suboptimal, their ease of execution overcomes all the preceding caveats, and they’re still a decent choice for those who don’t want finance to intrude more than is absolutely necessary into their lives. Choose the appropriate fund for your 401(k) contributions, and check your account balance only once or twice per year to safeguard against fraud.

You don’t have to pick the fund that’s assigned to your age. If you’re a young person who doesn’t tolerate stock risk well, there’s nothing wrong with choosing a more conservative fund. By the same token, if you’re a retiree with a low burn rate and high risk tolerance, you can pick one of the more aggressive funds.

It’s also worth noting that Vanguard also offers four “life strategy” funds, similar to the retirement date offerings, but which do not lower their exposure with age. The most conservative fund has a 19% stock exposure; the most aggressive has an 80% stock exposure. The life strategy funds’ expense ratios, which range between 0.11% and 0.14%, are a tad higher than the 0.08% for the target-date funds.

Global Couch Potato Land

With only slightly more effort, the individual investor can eliminate the drawbacks of target-date funds. As of this writing, Vanguard, BlackRock, and State Street (SPDR) offer total world index funds. In previous books, I’ve avoided recommending a capitalization-weighted world portfolio because of its high allocation to foreign equity, but at the current 61/39 domestic/foreign split, these funds are not a bad choice.

Say you have a $100,000 portfolio and you’ve decided on a 50/50 stock/bond split. Half ($50,000) goes into the total world index fund. What about the other $50,000? Almost any total bond market index fund with a relatively short duration will do; a short-term Treasury fund is safer still.

Because of its corporate holdings, a total bond index fund offers slightly higher returns than a Treasury fund of the same duration. For example, Vanguard’s short-term bond index fund has bested its short-term Treasury fund by about 0.3% to 0.5% per year, depending on the period examined.

However, in the teeth of the global financial crisis (GFC) in the fall of 2008, the short-term bond index fund lost a few percent. The equivalent Treasury fund, which holds no corporate bonds, rose by a few tenths of a percent. While that’s not a big difference, the Treasury fund holders likely slept a bit better than the total bond market holders. When the time came to take a deep breath and purchase stocks at the fire sale, the former felt better selling the bond fund without having to take a loss to do so.

Finally, you can close a bit of the Treasury/total bond fund return gap. Avoid Vanguard’s Short-Term Treasury Index Fund Admiral Shares’s 0.07% fee by purchasing the Treasuries on your own at auction. This can be done commission-free at most of the big fund companies, including Vanguard. Is that worth spending the perhaps half hour per year it takes to maintain a Treasury ladder? It depends on the size of your portfolio. With $50,000 in bonds, you’re saving $35 per year; with $500,000, you’re saving $350 per year. (The expense of the fund’s ETF shares is even lower at 0.04%, but sports a bid/ask spread and an occasional premium/discount.)

Ascending the Complexity Ladder

Let’s start with the simplest of the stock allocation just described, a total world stock market fund:

Images   100% Total World Stock Market

Next, let’s break that into US and foreign stocks:

Images   65% US Total Market

Images   35% Total International

Then break the foreign into developed and emerging funds:

Images   65% US Total Market

Images   25% International Developed Market

Images   10% Emerging Market

Then further break the developed market funds into Pacific and Europe:

Images   65% US Total Market

Images   12.5% European Market

Images   12.5% Pacific Market

Images   10% Emerging Market

Then add some ancillary asset classes:

Images   50% US Total Market

Images   10% REITs

Images   2.5% Energy Stocks

Images   2.5% Precious Metals Stocks

Images   12.5% European Market

Images   12.5% Pacific Market

Images   10% Emerging Market

And, finally, add some tilt:

Images   37.5% US Total Market

Images   12.5% US Small Value

Images   10% REITs

Images   2.5% Energy Stocks

Images   2.5% Precious Metals Stocks

Images   10% European Market

Images   10% Pacific Market

Images   5% Developed Market Small Value

Images   7.5% Emerging Market

Images   2.5% Emerging Market Small Value

These percentages pertain only to the equity part of the portfolio. If you’ve decided on a 60/40 stock/bond split, then multiply all these numbers by 0.6, in which case your allocation for the last, most complex portfolio to the US total stock market would be 22.5% and to European equities, 6%.

Over the coming decades, how will each of these portfolios, from simplest to most complex, perform relative to one another? I would give a slight edge to the more complex, tilted portfolios, for two reasons. First, the “value spread” remains at historically high levels, with value stocks selling much more cheaply relative to growth stocks. Second, the more complex the portfolio, the greater the gains from portfolio rebalancing, a subject I’ll discuss shortly.

Finally, one peculiarity of the MSCI and FTSE indices used (respectively) by iShares and Vanguard is that if you break your stockholdings into four components—US, Europe, Pacific, and emerging markets—you exclude Canadian equities, which are in none of these four indices and which comprise 3% of world market capitalization.

At best, the superiority of the more complex portfolios is a 55/45 wager. Further, the last one is very thinly sliced. At a 60/40 stock/bond mix, the allocations to energy, precious metals, and emerging markets small value stocks are each just 1.5% (0.6 × 2.5%). With a low six-figure portfolio, that’s hardly worth the trouble for all but the most devoted asset class junkie.

On the bond side, things are simpler. A bond portfolio’s workhorse should be either a short-term Treasury fund or your own hand-built ladder. Better yields can often be had from bank certificates of deposit, which also carry a government guarantee below $250,000. When purchased individually from the issuing bank, they usually offer an “option” on rising rates with the payment of a modest early termination interest penalty. Many investors prefer the convenience of buying CDs in a brokerage account, but selling one before maturity will incur a significant price penalty if rates have risen.

WHY REITS, PRECIOUS METALS, EQUITY, AND ENERGY STOCKS?

The shares of real estate investment trusts provide nearly all their long-term return in the form of dividends. Most of them are taxed at the ordinary income rate and should be held only in tax-sheltered accounts. They tend to perform well in the aftermath of tech bubble collapses. During the horrendous decade between 1999 and 2008, for example, they provided investors with a total return of 107%, as compared with a loss of 13% in the initially tech-heavy S&P 500. Be aware, though, that REITs constitute about 4% of most broad-market indices and around 10% of small-cap indices, although a few passive fund providers, like Avantis and Dimensional, largely exclude them from their domestically tilted funds.

Energy stocks and precious metals equity (PME) are recommended only for those who tolerate portfolio complexity and want protection against unexpected inflation, a cat that may already be out of the bag at the time of this book’s publication. As covered in Chapter 4, commodities futures funds suffer from crowding/contango (the upward slope of futures prices), which eats into their long-term returns. In contrast, while the shares of commodity-producing companies correlate with those of the broader stock market, in the long run, they do well during inflationary periods, as seen in Table 2.1.

PME is an especially thorny asset class. It has suffered share price losses of 70% or more three times during the past six decades, but it’s precisely this volatility that recommends it to those with a cast-iron stomach for risk, despite a real return of 0%–2%, depending on the time period. The relatively large purchases mandated by portfolio rebalancing during the severe downdrafts eventually sow the seeds for large gains during the bounce backs, which saw a rapid tripling of share prices from each of the three market bottoms. Needless to say, this asset class requires nerves of steel and the patience of Job, is appropriate for only the most enthusiastic of asset class junkies, and in any case should constitute no more than a few percent of your portfolio. The yellow metal itself has actually provided slightly higher returns than PME, but is not nearly as volatile. Gold requires a much higher portfolio allocation than PME to provide the same degree of diversification as PME, and it thus yields less of a “rebalancing bonus.”

BONDS/FIXED INCOME

Even in taxable accounts, municipal bonds don’t offer that much of an advantage. Because of their risks and the considerable expense of owning individual bonds, they should be held in a mutual fund. They can default in bad times, because they are backed only by their issuing authority. Even the rumor of default can crater their price. During the fall of 2008, even the shortest maturity municipal bonds saw price falls of around 3%. I would limit your exposure to munis to less than a third of your bond holdings.

CHAPTER 7 SUMMARY

Images   Many roads lead to asset allocation Jerusalem, but you can’t know in advance which will yield the highest risk-adjusted returns.

Images   Your equity allocation should be “reasonable.” It should center mainly on broad domestic and foreign markets and not grossly overemphasize small cap, REIT, or precious metals stocks.

Images   More important than portfolio complexity and precise allocations is your ability to stay the course through thick and thin. Never forget that a suboptimal allocation you can execute is better than an optimal one you can’t.

* The “volatility advantage” of periodic investments in small/value tilted portfolios is discussed in much greater detail in The Ages of the Investor.

PILLAR TWO

The History of Investing

When Markets Go Berserk

A knowledge of history is not essential in many fields. You can be a superb physician, accountant, or engineer and know little about the origins and development of your craft. Contrariwise, the practice of diplomacy, law, and military service demand a solid grounding in those fields’ pasts. But in no endeavor is Santayana’s dictum, “Those who cannot remember the past are condemned to repeat it,” more true than in finance.

Flying aircraft provides an apt analogy. While it’s possible to be a passable pilot without knowing anything about aviation history, the competent aviator assiduously reads accident reports; as the late admiral Hyman Rickover put it, “It is necessary to learn from others’ mistakes; you will not live long enough to make them all yourself.”¹

Financial history serves as the investor’s accident reports. Just as turbulent weather or an engine malfunction can bring a pilot and her passengers to grief, from time to time, the markets go barking mad and many investors suffer ruin. Always remember Charlie Munger’s first rule of compounding: never interrupt it. When the markets do go mad, a knowledge of the past will inform your decision-making and supply the fortitude to prevent that interruption.

Manias and panics used to occur about once a generation, but during the past quarter century we’ve seen no fewer than three episodes in the United States: the tech/internet mania of the 1990s, the real estate bubble of the early 2000s, and the recent frenzies surrounding cryptocurrency and meme stocks. The investor who was aware of the eighteenth-century South Sea bubble, the nineteenth-century railway bubble, and the Roaring Twenties stock bubble would likely not have been snookered by the frenzies of the past few decades.

Markets can crash, but it is less well known that they can remain depressed for decades at a time. This section’s chapters will deal with the periods of euphoria and depression that occur on a fairly regular basis. The average investor lives through at least a few markets of both types.

Even with an appreciation of their behavior, dealing with both buoyant and morose markets is difficult, and sometimes even the best-prepared cannot stay the course. But if you don’t prepare at all, you are doomed to fail.

The following chapters discuss the relevance of capital market evolution over the millennia and what markets look like when they go bonkers on the upside and on the downside.

CHAPTER 8

A BRIEF HISTORY OF FINANCIAL TIME

Since the dawn of civilization, farmers, traders, and merchants have needed capital to set up their operations before they start to bring in revenue.

The first organized long-distance trade involved commerce in bulk goods within the ancient Fertile Crescent. The alluvial plains of Mesopotamia produced large quantities of grain but were poor in metals. The opposite was true of the civilizations of the Persian Gulf, a disparity that gave rise to a high-volume trade in these two commodities. These maritime expeditions required substantial funding, and the participating merchants and their lenders blessed future financial historians by recording their financial arrangements on durable clay tablets.²

Most ancient funding was agricultural. Loans to farmers were often made interest-free but came attached to draconian collateral—the enslavement of the debtor’s children or of the debtor himself—presumably with the prospect of making a handsome profit in the event of default.

By the second century BCE, Mesopotamian legal code set maximum interest rates: 33.33% per year for grain and 20% for silver. Over the ensuing millennia, interest rates tended to fall, to as low as 4% at the height of the Roman Empire.³

Why even briefly discuss remote financial history, particularly the gradual and uneven fall in loan rates in the ancient world? First, to demonstrate that the story of the capital markets is at least as old as the written word, and second, because that ancient history is directly relevant to the low expected returns that characterize today’s stock and bond markets.

As societies become prosperous, investment returns of necessity fall. Imagine a subsistence-level society plodding along at the precipice of starvation. Such a society has little excess capital. Nearly every last basket of grain, head of cattle, and piece of silver goes for food and shelter. Even subsistence societies, though, need capital for seed, implements, and housing, and its owners can charge the earth for it. In early agrarian societies, as we’ve just seen, the cost of capital was high indeed. The rich farmer could lend his grain or livestock at a prodigious rate of interest, and modern anthropological data in aboriginal societies suggest a prehistoric annual rate of interest of about 100 percent: a pig or sack of rice loaned out paid back twice over a year later.⁴

As an economy becomes more productive, wealth slowly accrues in the purses of the fortunate few with grain, domesticated animals, and money to spare. Capital becomes more plentiful, not only in an absolute sense, but also relative to the need for it: the very definition of a “wealthy” society is one with lots of capital to spare. At the same time, the legal institutions of these increasingly wealthy societies advanced to govern the rules applied to borrowing and lending. A major part of the famous Babylonian Code of Hammurabi (ca. 1750 BCE) governed commercial behavior and interest rates, which must have made loans safer and lowered rates yet further.

Before about 1200 CE, loans were a personal matter between the borrower and lender. In the late twelfth century, Venice saw the first glimmer of public debt markets when the fledgling republic imposed forced loans, prestiti, from wealthy citizens. In 1262 these loans were consolidated into a single fund, the Monte Vecchio (literally, “old mountain” [of debt]), which paid its unwilling investors semiannual payments of 2.5%: 5% per year. Although the republic did not issue certificates for the prestiti, it recorded their ownership in a central loan office, and, critically, prestiti could be transferred to others. Over time they became well enough known and trusted that they traded well beyond the borders of the Venetian Empire.⁵

Since the 5% interest payment was usually below the prevailing interest rate, the forced purchase of prestiti represented a tax on the wealthy, and the price at which they changed hands reflected this. The prestiti never matured; in financial terms, they were a “perpetuity” whose market value was calculated by dividing the interest payment by the interest rate. If the prevailing rate of interest was 5% and the prestiti yielded 5 ducats of annual income, then it was worth (5 ducats)/0.05, or 100 ducats. If the prevailing rate of interest rose to 10% because of war or political instability, then the prestiti value fell to (5 ducats)/0.10, or 50 ducats. At several points between 1300 and 1500, the republic was threatened enough that prestiti prices fell well below 50 percent of their face and represented a hefty effective tax on the wealthy aristocrats and merchants forced to buy them. (See Figure 8.1.)

FIGURE 8.1 Prestiti prices, 1300–1500

Source data: Homer and Sylla, A History of Interest Rates

Since the Venetian loan office recorded the prices at which prestiti changed hands, we can observe for the first time how the price of a security for which there is a ready market responds to social and economic conditions.⁶

For several decades after the prestiti were first issued, prevailing interest rates were not much above 5%. For example, in the relatively tranquil year of 1375, they sold for a price of 92.5% of face value at a yield of 5.41% (5%/0.925).

Between 1377 and 1380, Venice fought a devastating war with Genoa. Initial financing needs drove prices as low as 19% of face value, recovered briefly, then fell almost as low again when in 1379 the Genoese penetrated the Venetian Lagoon, captured the city of Chioggia at its southern edge, and blockaded Venice itself. By 1380, just as the Venetians seemed ready to capitulate, they launched a daring counterblockade of Chioggia, forced the Genoese to retreat and, more important for our purposes, drove a powerful recovery in prestiti prices.⁷

The price history of prestiti at a time of high geopolitical and economic turmoil illustrates the intimate entanglement of risk and return. Investors who purchased prestiti when things looked the worst easily doubled their money, but at the time it seemed even more likely that Venice was done for, and the resultant total financial loss would have been the least of their problems.

The same thing happened in Britain between 1789 and 1814, when revolution, anarchy, and war lapped on its shores and drove the rate on both short- and long-term bonds above 5% in gold-backed currency. In both 1931–1932 and 2008–2009, the US economy imploded and threatened the very viability of American society, which consequently depressed stock prices. Had things turned out a bit differently, the investor who bought stocks at either of those times might have lost everything. But on all three occasions, as in Venice in 1380, Lady Luck smiled on the capital markets. To illustrate, each dollar invested in the S&P 500 at the market bottom on March 9, 2009, grew to $7.33 at year-end 2022. Investing at such times plays financial Russian roulette at a million dollars a throw; five times out of six, you will be well rewarded. But only play with money you can afford to lose. History occasionally plays cruel tricks, as it did to British investors who bought bonds yielding 2% at the height of England’s power just prior to World War I, only to see the pound detach from gold and inflate away their bonds’ real value. In other words, investing during the worst of times pays off most of the time, but occasionally there’s a bullet in the chamber.

The behavior of security returns in fraught times, such as 1380 and 2009, teaches the historically informed investor that the best fishing is usually done in the roughest waters, and that waiting for the geopolitical, financial, or epidemiological environment to improve is most often a fool’s errand, since the biggest returns will already have been made by the time the sky begins to clear. Unless it doesn’t.

***

After 1200, the real bond and loan yields continued to fall, though the process has been noisy. Recently, Harvard doctoral candidate Paul Schmelzing constructed an extremely detailed series of loan rates in eight nations with large economies and long historical records: Italy, Netherlands, Germany, France, Spain, England, Japan, and the United States. Figure 8.2 summarizes his data in graphical form.⁸

FIGURE 8.2 The slow fall in risk-free interest rates over the past seven centuries

Source data: https://scholar.harvard.edu/pfschmelzing/data-0

Beginning in 1311, I adjusted the nominal rate in each year for each nation for that year’s inflation, averaged the loan data for nation-states extant in that year, and then smoothed those data points over the preceding decade.

Over the past seven centuries, rates have fallen from about 17% to about zero, a decrease of more than 2% per century. Schmelzing’s more granular estimate of this slow secular decrease in the risk-free rate is 0.6%–1.8% per century. Presumably the wide bounds of this estimate are due to the volatility in the real rate seen in the past two centuries related to the Napoleonic Wars and abandonment of the gold standard after the 1930s. For a while during the 1980s, as central banks jacked up real interest rates to cool off inflation, the risk-free rate blessed conservative fixed-income investors with high returns. By 2021, that lagniappe had disappeared into the rearview mirror, and the centuries-long downward march in real bond yields had resumed, arriving at, and perhaps below, zero. In Schmelzing’s dry doctoral thesis prose, “the zero lower bound can be expected to become a permanent and protracted monetary policy problem. [My data] does not support those who see an eventual return to ‘normalized levels’.”⁹ Translation: don’t hold your breath for a permanent return to the world in which Treasury bill yields match inflation, and in which Treasury note and bond yields exceed it by a comfortable margin.

Nonetheless, in the summer of 2022, the Federal Reserve increased interest rates to the point that real yields, as reflected by Treasury Inflation-Protected Securities (TIPS), touched 2%, which corresponds to the real return of US Treasury notes and bonds before the twenty-first century. As of writing, whether or when they fall back to Schmelzing’s zero real yield forecast is anyone’s guess.

To summarize: over the past five millennia, interest rates have been falling, a process that has accelerated over the past several centuries. As discussed, the main reason for falling bond returns is that as societies become wealthier, capital becomes more abundant relative to the need for it, a phenomenon that former Fed chairman Ben Bernanke labeled a “savings glut.”¹⁰

There’s a second reason for falling returns: increasing life expectancies. Irving Fisher summarized this relationship in one word: impatience.¹¹ A cheeseburger now or two in 10 years? How many cheeseburgers you demand for future delivery depends in large part on how hungry you are and, to a lesser extent, how healthy and well housed you are: in short, how impatient you are for a cheeseburger. The better fed you are, the fewer future cheeseburgers (i.e., the lower the interest rate on your savings) that you’ll demand.

In the ancient and medieval worlds, generally starving and poorly housed populations with short life expectancies were highly impatient for consumption and demanded higher interest rates for their capital than did better-fed, better-housed, and longer-lived modern populations, who must squirrel away enough for retirements that may last longer than their working careers. With apologies to Samuel Johnson, a man who is to be hanged in a fortnight demands a high rate of return on his savings.

There’s yet a third reason for lower modern interest rates: lower transaction costs. Before the prestiti, nothing existed that looked even remotely like today’s bond markets. Individual creditors might occasionally transfer an existing debt contract to a third party, but no ready market for outstanding debt contracts existed. Ancient societies offered its rare capitalists—the lucky few with spare grain, animals, or silver—high returns, not only because capital was scarce, but also because of what we today call intermediation costs: ancient investors had to go out and find their own borrowers. Doing so without the benefit of modern communication technology required great effort, and only a high rate of return justified the work involved. Modern investors can acquire their own minuscule slices of the whole world’s security markets with a few keystrokes, and thus should not expect to be as well rewarded for such minimal effort.

***

Most of the discussion so far has focused on the returns for debt. What about stocks? Although commercial partnerships, particularly involving families, were a familiar feature of ancient Greece and particularly ancient Rome, whose laws defined various classes of business organizations, loosely referred to as societates, scant evidence can be found of trading in their shares. (A commonly repeated myth had shares in tax farming companies trading in the Temple of Castor and Pollux in the Roman Forum, but documentary evidence for this ancient stock market is lacking.)¹² If ancient investors wanted exposure to equity ownership, they had to become partners in a business.

The establishment of markets for equity developed at approximately the same time as the debt markets of Venice. About a century before Venetians bureaucrats started tracking prestiti ownership, the French city of Toulouse built a series of water mills, known as the Bazacle mills, to capture the power of the vast Garonne River. The system consisted of several dozen floating mills, initially constructed around 1071, which were converted to land mills by 1190. They were one of the technological marvels of their age—the equivalent of today’s Apple or Tesla.

The following two centuries saw the construction of multiple competing mills, whose flows interfered with each other. In 1372 these companies merged into the Honor del Bazacle, and its shares began to trade. Critically, the sale of its shares did not require the approval of the company’s management, although shareholders were required to occasionally serve on its board of directors. In 1888 the company converted from milling to hydroelectric generation; over the centuries, the value of the shares very roughly kept up with inflation and yielded a dividend averaging 5%. In 1946, the French government, apparently not caring much for economic history, nationalized the company and extinguished its shares.¹³

By the early medieval period, then, the Europeans were trading both debt securities (prestiti) and stock shares (Honor del Bazacle). All that was lacking was a formal venue dedicated to the exchange of those securities, a gap filled in 1602 when the Dutch East India Company founded the Amsterdam Stock Exchange on the site of a sixteenth-century bourse (commodities exchange) to host trading in its shares.¹⁴

Is the long-term trend of real expected stock returns, like that of bonds, trending down? We don’t know, for at least two reasons. First, the equity markets supply the economic historian with a lot less data than for bonds. For example, until about 1800 only two stocks, of the Dutch East and West India companies, regularly traded in Amsterdam. (A third trading company, the Society of Berbice, traded between 1734 and 1752.)¹⁵ Similarly, in London before 1823, high-quality price series are available for the shares of only three companies: South Sea, England’s East India Company, and the Bank of England.¹⁶

Solid data about stock returns across multiple nations begin only in 1900, and they show a remarkably uniform equity risk premium of approximately 4%–5%. The problem with this estimate is that in almost all countries in the data set, about 1% of that 4%–5% came from increasing valuations and cannot be expected to recur, which likely reduces the expected equity risk premium to 3%–4%, about what I estimated in Chapter 1 from dividend yields and dividend growth.

At best, this sort of estimate only gets the investor into the ballpark. If the standard deviation (SD) of US stocks is about 16%, then over the next 30 years, the 95% confidence limits around a central estimate of an inflation-adjusted 3.5% per year are between −2.3% and +9.3% per year.*

CHAPTER 8 SUMMARY

Although the histories of debt financing and equity in business partnerships span millennia, secondary markets for these go back only several centuries. Over the course of recorded history, the returns to investing have fallen for three reasons:

Images   The rapid increase in wealth produced by technological innovation yields an asymmetry between the supply of and demand for capital—Benjamin Bernanke’s “savings glut”—that drives down interest rates.

Images   People are living longer. Citizens of modern societies expect a prolonged period of retirement, a concept unknown until the nineteenth and twentieth centuries. This phenomenon has produced a mountain of global retirement savings that further drives down interest rates.

Images   Finally, over the past several centuries, trading costs for investments of all types have fallen, a process that has accelerated dramatically in the past several decades to the point of near disappearance. A world in which a widely diversified portfolio of the entire planet’s stocks and bonds can be purchased in less than a minute for a few hundredths of a percent annual expense makes those securities more widely available and thus drives their prices up and their expected returns down.

The modern investor should be philosophical about this seemingly gloomy conclusion. At first glance, one might envy the Mesopotamian capitalist earning a 20% return on a silver loan or the 1920s investor who benefited from the high subsequent stock returns.

But both of their worlds were by today’s standards dangerous and miserable places to live, full of marauders, poor sanitation, and inconveniences that would not be tolerated by even the poorest modern inhabitants of today’s developed nations. Better a world with low investment returns but in which starvation has been largely banished, where transport presents only a slight mortal risk, and in which young people are not struck down in the prime of life by easily treated bacterial diseases, than a world with high returns permeated with those mortal blights.

* If the SD of annualized returns is 16%, then the SD for 30-year annualized returns is 2.9% (16%/sqrt[30]). Since the 95% confidence limits fall between −2SD and +2SD, these correspond to 3.5% plus or minus 5.8%.

CHAPTER 9

TOPS

The History, Pathophysiology, and Diagnosis of Manias

Three decades ago, I got lucky. I came across a book originally written in 1841 by a Scottish journalist named Charles Mackay, Memoirs of Extraordinary Popular Delusions and the Madness of Crowds. Its first three chapters, which described the Mississippi Company, South Sea, and Dutch tulip episodes, fascinated me. Although I thought Mackay’s narratives irrelevant to the relatively well-behaved capital markets of the early 1990s, I wondered what must it have been like to have lived back then. As Harry Truman said, “The only thing new in the world is the history you don’t know”; over the next several years, I found out as Mackay’s descriptions of financial madness came to life before my amazed eyes.¹

The book’s purchase turned out to be the best investment I ever made. When the madness of the dot-com bubble rolled around, I had read the script and I knew how the movie ended. I suspect that the book, which has been continuously in print since its first publication, has proved just as salutary to many thousands of others. The early twentieth-century financier Bernard Baruch claimed that Mackay had saved him millions and was so impressed that he wrote the foreword to the book’s 1932 printing.²

In this book’s 2002 first edition, I wrote of dot-com stocks, “If we were not personally touched by these shooting stars, we all knew people who were.” In the early 2000s, the boom and its subsequent collapse permeated the public investing consciousness and needed no further introduction from me.

Today, mention of that episode usually draws blank stares from audience members below the age of 40. Even older people’s memories have faded. Although the famous Einstein quote about compound interest being the most powerful force in the universe is apocryphal, he could have said the same thing about amnesia. Financial amnesia erodes our perspective on the markets. It logically follows that combating that entropy with a deep and abiding interest in financial history should pay a rich stream of dividends.

This chapter will summarize the largest and most well-known historical manias and discuss them from the perspective of the relevant evolutionary psychology, social psychology, and financial pathophysiology, and also of their diagnostic features. This exercise just might prevent you from getting snookered during the bubbles that you’ll almost certainly encounter in your investing future.

IN THE BEGINNING, TULIPS

Paradoxically, the Mackay book is most famous for its discussion of the 1630s Dutch tulip mania. Alas, the tulip chapter has earned the scorn of modern historians, who believe that although the tulip mania was a genuine bubble, it was hardly the society-wide phenomenon Mackay described.³

DIVING FOR DOLLARS

In 1687, a New England sea captain named William Phips docked in England with 32 tons of silver raised from a Spanish pirate ship, enriching himself, his crew, and his backers beyond their wildest dreams. Soon enough, entrepreneurs applied for and were granted patents for a variety of “diving engines” and floated shares in diving ventures. Almost all of these patents were worthless, submitted for the express purpose of creating interest in their companies’ stock. The ensuing ascent and collapse of the diving company stocks, culminating about 1689, could be said to be the first tech bubble. Daniel Defoe, of Robinson Crusoe fame, was the treasurer of one of those companies. His insider knowledge of their workings did not prevent his bankruptcy—one of the most spectacular of the age.

The diving companies never deployed any credible operations, let alone produced any revenue. This quickly became apparent to investors, and the madness was soon over. We don’t have any records of exact prices and returns, but it’s a sure bet that the eventual result of investment in each of these companies was total loss. Aside from Phips’s enterprise, no diving company turned a profit, and it was not immediately clear how any of these companies could even access the treasure-laden wrecks. In modern parlance, all they had was a dubious business model.⁴

WHAT HAPPENED AFTER 1600?

I didn’t choose these vignettes at random. The appendix of financial economist Charles Kindleberger’s magisterial Manias, Panics, and Crashes lists 38 boom-and-bust cycles, beginning in 1618: 3 in the seventeenth century, 7 in the eighteenth century, 17 in the nineteenth century, and 11 in the twentieth century.⁵

So why the early seventeenth-century start date for bubbles? Two reasons. First, the birth of modern “fractional reserve banking” occurred when East India merchants arrived in London shortly after 1600 with hauls of gold and silver and no place to safely stash them. At that time, England had no banking system, but London was home to a number of goldsmiths, whose livelihoods demanded the safe storage of valuables. Merchants began to deposit their loot with the goldsmiths, who issued certificates of deposit, which then began to circulate as money. Soon enough, the goldsmiths tumbled to the happy realization that they could issue the certificates in excess of the amount of precious metal they held.

In other words, they could print money.

Since the prevailing interest rate was well over 10% per year, the goldsmiths made a good living loaning out the certificates, a process that held up only as long as a large number of certificate holders didn’t redeem them all at once. If the goldsmith’s safe held £10,000 of silver and he had issued £30,000 worth of certificates—one-third issued to the specie’s owners and two-thirds to borrowers—and the bearers of £10,001 of the certificates demanded payment in silver, the goldsmith was bankrupt. In fact, if the certificate holders even suspected that the goldsmith was in trouble, they could precipitate a disastrous run.

The leverage ratio in this example is 3:1. The higher this ratio, the more probable a run, which occurred at least four times between 1674 and 1688. Between 1677 and the establishment of the Bank of England in 1694, the number of London goldsmith-bankers fell from 44 to around a dozen. (Hence the word “fractional” in “fractional reserve banking”: the portion of certificates issued that were actually backed by silver.)

Over the decades, London’s goldsmith-bankers found a 2:1 ratio or below fairly safe. The system heralded the birth of an elastic money supply that could be adjusted according to the hunger of borrowers for loans and the willingness of creditors to lend. When borrowers and lenders were euphoric, the money supply expanded; when they were frightened, it contracted. The modern financial term for the amount of paper monetary expansion is “leverage”: the ratio of paper assets to hard assets.⁶

The increasing frequency of the nineteenth-century manias spurred the creation of the modern central bank. Despite the dramatic growth of the world economy, fiat money, and fractional reserve banking during the twentieth century, it’s notable that Kindleberger recorded only 11 cycles over its 100 years, likely due to increasing central bank intervention in the economy. He published Manias, Panics, and Crashes in 2000, just before the collapse of the dot-com mania. The twenty-first century saw the dot-com mania at its dawn, then the real estate mania/global financial crisis of 2007–2009, and finally the recent cryptocurrency bubble—about par for the once-per-decade course.

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The second reason for the appearance of financial bubbles after 1600 was the birth of the scientific method and the technological revolution it spawned, attendant to the 1620 publication of Francis Bacon’s Novum Organum Scientiarum (“new instrument of science” or in English, The New Organon). Before the seventeenth century, scientists (“natural philosophers,” as they were called) deployed the millennia-old Aristotelian deductive method that proceeded from axioms—unquestioned principles. In this intellectual framework, empirical observation counted for nothing. It was thus ill-suited to uncovering and exploiting nature’s mysteries.

In a radical departure from the ancient deductive method, The New Organon described an inductive process that compulsively collected data, which practitioners then tested against theory: the modern scientific method. Within decades, Bacon’s followers, most prominently Robert Hooke, Robert Boyle, and Isaac Newton, founded the Royal Society of London for Improving Natural Knowledge (now known simply as the Royal Society). Bacon’s movement spread throughout Europe and triggered a spectacular acceleration of scientific discovery.⁷

In the 1960s, economic historian Hyman Minsky put together these two post-1600 phenomena—elastic credit and the technological revolution wrought by Bacon and his intellectual children—into a compelling model of financial bubbles.

Minsky was not your average economist. He was a long-haired iconoclast who believed that capitalism was fundamentally unstable, prone to booms and busts. This instability happened, he thought, when two things occurred together: the easing of credit and the attendant fall in interest rates; and what he termed “displacement,” a compelling innovation that could be either technological or financial.

This is precisely what happened during the tulip mania. Beginning in the sixteenth century, the Dutch developed what historians have called “the first modern economy” featuring sophisticated banks, credit markets, and rapidly falling interest rates.⁸ The “displacement” involved was twofold. First, the Dutch bred tulip variants infected with viruses that imparted strikingly beautiful petal patterns whose rarity made them valuable. Second, complex futures markets for tulip bulb futures sprang up, which was where the speculation actually centered.

The same formulation applies to the diving company bubble. It’s no coincidence that the “displacement” caused by Phips’s great good fortune and the diving patents occurred simultaneously with the Glorious Revolution of 1688, in which Dutch Stadtholder William of Orange, at the invitation of English Protestants, invaded and established himself as King William. In one of history’s most felicitous compromises, William surrendered the divine right of kings in exchange for a secure tax base, which made English government debt more secure and dramatically reduced interest rates.

I would add two more bubble criteria to Minsky’s. The first is amnesia, “the most powerful force in the investment universe,” for the last bubble. As anyone with a parent or grandparent who lived through the Great Depression of the 1930s will attest, the financial caution born of market panics and hard times persists for decades. Any subsequent bubble requires a new crop of marks with no memories of those financial disasters. Consequently, bubbles are typically the province of the young, who are wont to tell their more skeptical elders that they “just don’t get it.”

The last criterion is the neglect of the time-honored and theoretically sound valuation methods described in Chapter 1, which must be abandoned to allow nosebleed bubble prices.

To summarize, the blowing of a bubble requires:

Images   Low interest rates

Images   Technological or financial innovation

Images   The passage of at least a few decades since the last mania

Images   The abandonment of traditional financial metrics

A FINANCIAL TALE OF TWO CITIES

The diving company bubble turned out to be the warm-up for the first global speculative orgy a generation later.

During the quarter century or so between the two episodes, England’s banking system, and with it, credit availability—the great bubble fuel—expanded rapidly. Once the warring nation-states of the late Middle Ages got a taste of the abundant military financing available from bond issuance, they could not get enough. The War of the Spanish Succession, which ran from 1701 to 1714, left France and Spain, and to a lesser extent England, with ruinous debt. By the early eighteenth century, Spain was hopelessly behind on its interest payments, and France was also deep in the hole.

Into this financial chaos arrived a most extraordinary Scotsman: John Law. The scion of a local goldsmithing family, Law had become familiar with fractional reserve banking at an early age. After escaping the hangman for killing a man in a 1694 duel, he studied the banking system in Amsterdam and eventually journeyed to France, where he ingratiated himself with the Duke of Orléans and founded the Mississippi Company.

In 1719 the Duke granted the company two impressive franchises: a monopoly on trade with all of French North America and the right to buy up rentes (French government annuities—i.e., bonds) in exchange for company shares. The rentes/shares exchange was particularly attractive to the Royal Court, since it relieved the government of its crushing war debts.

Law’s system contained one remarkable feature: the Mississippi Company issued money as its share price increased. The company issued its own currency, as did all banks of that time. His system provided the first of the necessary bubble ingredients: a major shift in the financial system caused by the liquidity of the company’s new banknotes. In 1720, as the Mississippi Company’s shares rose, it printed more notes, which purchased more shares, which increased its price yet more. Some investors made vast paper fortunes and observers coined the word “millionaire.” The frenzy spilled over the entire continent, where other investors floated new ventures with the vast amounts of capital now available.⁹

A fashionable new technology played a prominent role: the laws of probability. Pierre de Fermat and Blaise Pascal had recently invented this branch of mathematics, and in 1693, Astronomer Royal Edmond Halley (of Halley’s Comet fame) developed the first mortality tables. Insurance companies became all the rage and would figure prominently as the speculative action moved to London.

The English, amazed at the fortunes being made across the Channel and green with envy at Law’s marvelous new financial system, jumped on the bandwagon. A decade earlier, in 1710, the South Sea Company had actually exchanged government debt held by investors for its shares and had been granted the right to a monopoly on trade with the Spanish Empire in America. By 1720, a generation had passed since the diving company debacle.

In exchange for taking over its debt, the government also paid the South Sea Company an annuity, but neither the Mississippi Company nor the South Sea Company ever made significant money from their trade monopolies. The French company never really tried, and war and Spanish intransigence blocked British trade with South America. In any event, none of the South Sea’s directors had any experience with South American trade. The Mississippi Company was just a speculative shell. The South Sea Company’s situation was a bit more complex, as it did receive an income stream from the government.

The South Sea Company’s deal with the government was structured in a most peculiar manner: it was allowed to issue a fixed number of shares that could be exchanged for the government debt it bought from investors. In other words, investors could exchange their bonds, bills, and annuities for stock in the company. The higher the share price of the company, the fewer the shares it had to pay investors and the more shares that were left over for the directors to sell on the open market.

Inflating the price of South Sea shares in this manner thus benefited the company, and the liquidity sloshing through the European financial system in 1720 facilitated this dynamic. At some point the share price took on a life of its own, and investors were happy to exchange their staid annuities, bonds, and bills for those of rapidly rising shares. In the summer of 1720, share values peaked on both sides of the Channel. South Sea’s last subscription was priced at £1,000 and was sold out in less than a day. (The stock price, with a par value of £100, stood at about £130 at the start of the bubble.)

The government became alarmed at the rapidly rising share price, and some gray heads still remained who had lived through the diving company episode. Parliament proposed limiting the share price. The company stymied the proposal by providing under-the-table shares to various notables, including the king’s mistress, and the price limitation was scotched. The shares turned out to be counterfeit.

The most fantastic manifestation of the speculation was the appearance of the “bubble companies.” The easy availability of capital produced by the boom allowed all sorts of dubious enterprises to issue shares to a gullible public. Most of their schemes were legitimate but ahead of their time, such as a company formed to settle Australia and its environs (a half-century before Captain James Cook first reached the continent), another to build machine guns, and yet another that proposed building ships to transport live fish to London. Others were patently fraudulent, and still others lived only in later legends, including a famous mythical company chartered “for carrying on an undertaking of great advantage but no one to know what it is.”¹⁰ Only 2 of the 190 recorded bubble companies succeeded: the insurance giants Royal Exchange Assurance and London Assurance.

Both bubbles burst in 1720. As Ernest Hemingway famously said, bankruptcy occurs in “Two ways. Gradually, then suddenly.” In early 1720, the Prince of Conti, miffed at not being allotted enough Mississippi stock, demanded that Law’s Banque Royale exchange its new paper money for three wagons filled with the gold and silver coin that supposedly stood behind the notes. Law, recognizing Conti as the wolf at the door, had the regent force the unpopular prince to back down. It was too late. Perceptive investors realized that the game was up and precipitated a full-fledged run on the bank.¹¹

The English bubble’s collapse was more complex. In June 1720, the South Sea Company, angry over competition for capital from the bubble companies, had Parliament pass the Bubble Act. This legislation required all new companies to obtain parliamentary charters and forbade existing firms from operating beyond their charters. Many of the insurance companies, which helped sustain the frenzy by lending substantial amounts to South Sea Company shareholders, started out in other lines of business, and the Bubble Act shut off the flow of funds from them. Prime among the companies extending credit to South Sea and its shareholders was the Sword Blade Company, which, naturally enough, was chartered only to make swords. The legislation pricked the bubble by forcing Sword Blade’s withdrawal from the financial markets. By October, it was all over. Isaac Newton, having made then lost a fortune in South Sea stock, supposedly said that while he could calculate “the motions of the heavenly bodies,” he could not “calculate the madness of the people.”¹²

England Gets Taken for a Ride

One of history’s most spectacular examples of Minsky’s “displacement” was the railroad, a technological marvel that was both revolutionary and highly visible. Until steam power arrived in the nineteenth century, long-distance overland travel was almost exclusively the province of the rich. Only they could afford the coach companies’ exorbitant fares, or if truly wealthy, their own coach-and-six. Even then, poor road quality and public safety problems made travel a dangerous, slow, and extremely uncomfortable endeavor.

English railroad historian John Francis described the state of premodern transport:

The machines which were employed to convey produce, rude and rough in their construction, were as heavy as they were clumsy. Even if the roads were tolerable, it was difficult to move [those machines], but if bad, they were either swallowed in bogs, or fell into dykes: sometimes, indeed, they sunk into the miry road so deep, that there was little chance of escape until the warm weather and the hot sun made their release easy. Markets were inaccessible for months together, and the fruits of the earth rotted in one place while a few miles off the supply fell far short of demand. . . . It was found cheaper to export abroad than to convey produce from the north to the south of England. It was easier to send merchandise from the capital to Portugal, than to convey it from Norwich to London.¹³

At a stroke, the railroads made overland travel cheap, safe, rapid, and relatively comfortable. Even more important, the steam engine was undoubtedly the most dramatic, romantic, and artistically appealing technological invention of any age (aside from, perhaps, the clipper ship). Fanny Kemble, a famous actress of the period, captured the mood precisely after her first trip on George Stephenson’s Rocket. She found it:

. . . a snorting little animal which I felt inclined to pat. It set out at the utmost speed, 35 miles per hour, swifter than the bird flies. You cannot conceive what that sensation of cutting the air was; the motion as smooth as possible. I could either have read or written; and as it was I stood up and with my bonnet off drank the air before me. When I closed my eyes this sensation of flying was quite delightful and strange beyond description. Yet strange as it was, I had a perfect sense of security and not the slightest fear.¹⁴

The public sensation surrounding rail travel was unimaginable to the modern reader—it was the jet airliner, personal computer, internet, and fresh-brewed espresso all rolled into one. The first steam line was established between Darlington and Stockton in 1825; in 1831, the Liverpool and Manchester Line began producing healthy dividends and soaring stock prices. This euphoria created a bull market in railroad stocks, followed by a sharp drop in prices in the bust of 1837.

A subsequent stock mania, the likes of which had not been seen in Britain before or since, ensued when Queen Victoria made her first railway trip in 1842. Her ride ignited a popular enthusiasm for rail travel that even modern technology enthusiasts might find difficult to fathom. Just as people spoke reverently of “internet time” during the late 1990s, in the 1840s “railway time” was the operative phrase. For the first time, people began to talk of distances in hours and minutes, instead of days and miles. People were said to “get up a head of steam.”

By late 1844, the three largest railway companies were paying a 10% dividend; by the beginning of 1845, 16 new lines were planned and 50 new companies chartered. These offerings usually guaranteed dividends of 10% and featured members of Parliament and aristocrats on their boards, who were generally paid handsomely with under-the-table shares. Dozens of magazines and newspapers were devoted to railway travel, supported by hundreds of thousands of pounds in advertising for the new companies’ stock subscriptions. Nearly 8,000 miles of new English railways were planned—four times the nation’s existing trackage.

By late summer 1845, with existing shares up 500%, promoters registered at least 450 new companies. Entrepreneurs appeared out of nowhere to project railways around the globe, from Bengal to Guyana, with more than 100 new lines in Ireland alone. In the latter part of the bubble, lines were planned literally from nowhere to nowhere, with no towns along the way. The role played by low interest rates in this orgy of speculation was obvious. As Walter Bagehot would later write, “John Bull can stand many things, but he cannot stand two percent”; that is, low interest rates on safe assets cause capital to flee toward speculative investments.¹⁵

The Minsky “displacement” here was obvious. Credit was abundant. In the 1840s, it took the form of the subscription mechanism of purchase, in which an investor “subscribed” to the issue for a small fraction of the purchase price and was subject to “calls” for the remaining price as construction capital was needed. As with all bubbles, a sudden credit contraction punctured this one. By 1845, with building underway, investors sold existing shares to meet calls for capital. By mid-October 1845, it was all over. Reporting the fiasco, the Times of London introduced the word “bubble” into popular financial lexicon when it proclaimed:

“A mighty bubble of wealth is blown away before our eyes.”¹⁶

THE ROARING TWENTIES

The 1920s stock bubble was pure Minsky. First, it had displacement in spades: The early twentieth century saw a rate of innovation second only to that of the post-Napoleonic period. The aircraft, automobile, radio, electrical generator, and the devices it powered—most important, Edison’s light bulb—all burst upon the scene within a few decades. Second, an expansion of credit loosened the investment floodgates.

If singular blame for the 1920s stock bubble can be assigned, it probably belongs to Winston Churchill. As chancellor of the Exchequer, he reinstated the gold standard and fixed the pound sterling at its prewar value of $4.86. Because of Britain’s wartime inflation, this was a gross overvaluation and made British goods overly expensive abroad and foreign goods correspondingly cheap. The result was a gross trade imbalance that rapidly depleted the British Treasury of gold. The traditional solution for a trade imbalance is to have your foreign trading partners reduce their interest rates. Because low rates make investing in your partners unattractive, money flows out of those countries back to yours, which restores the trade balance.

Unfortunately, low interest rates in the United States also expanded credit. In 1927, the United States was in the middle of an economic boom, and the last thing its overheated economy needed was easier loan money brought about by the lowered American interest rates requested by the British. Most American financial authorities realized that this was an awful idea. Unfortunately, Benjamin Strong, the chairman of the Federal Reserve Bank, and Montagu Norman, the governor of the Bank of England, were close personal friends. Strong, who dominated the Federal Reserve, threw gasoline on the fire by lowering interest rates.¹⁷

The third bubble ingredient was already in place, too. It had been more than 20 years since the last market crash in 1907, which saw stock prices fall by 48%, and not enough gray heads were left to warn about the risks of stock speculation. Almost simultaneously, the final component of the mix was added as millions of ordinary citizens, completely ignorant of the principles of asset valuation, were sucked into the stock market by the irresistible temptation of watching their friends and neighbors growing effortlessly rich. They were joined by tens of thousands of professionals who should have known better. Over the subsequent two and a half years, stock prices rose more than 150% before the infamous “black days” of October 1929 saw stock prices fall, once again, by 48% from their late summer high and then continue to fall to one-tenth of their peak 1929 prices less than three years later.

WHY MANIAS?

It should be painfully clear by now that bubbles and busts have become an inevitable feature of financial markets ever since the seventeenth century, when English goldsmiths invented fractional reserve banking.* Simultaneous with that, Bacon invented the scientific method, which in turn yielded a steady stream of Minsky’s “displacement,” and with it, the wealth of the modern world.

Minsky, who died in 1996, had taught that this cycle is the inevitable result of an elastic currency in which banks, both the government central one (the Federal Reserve) and private ones, can expand and contract the supply of money. Further, he understood that this monetary expansion and contraction occurs in just about all areas of the market economy, not just in housing, but in corporate management and in the stock and bond markets as well.

Minsky’s famous “instability hypothesis” states that in a safe and stable financial environment, conservative bankers, cognizant of the profits made by their less cautious brethren, begin to lend to riskier borrowers and initiate a cycle of ever-lower lending standards.

Eventually, loan risk gets out of hand and a blowup occurs, lenders and investors rediscover prudence, and the cycle begins anew. The process seems to play out, very roughly, once per decade. In short, stability begets instability, and instability begets stability, with borrowers and lenders dancing together through jitterbugs of greed and tangos of fear.¹⁸

Not only does the intrinsic nature of the financial markets make them susceptible to manias and crashes, so does human nature itself, and while it’s possible that modern central banking has muted these cycles, it’s also possible that central bankers’ recent propensity to heroically respond to economic downturns with novel monetary tools such as quantitative easing may, over the past few decades, have made bubbles more frequent.

Mackay’s famous book recounted mass delusions in domains well beyond finance: religion, dress, health, facial hair, and even murder by poison. As the recent QAnon belief system—a conspiracy theory believed by as much as 20% of the US population—shows, we haven’t exactly outgrown this alarming tendency.

Just what is it about human nature that predisposes us to mass delusions? At the risk of being overly glib, the human species is the ape that imitates and the ape that tells stories.

About 50,000 to 100,000 years ago, modern humans departed northern Africa to inhabit all of the continents except Antarctica. Even more remarkably, beginning around 10,000 BCE, humanity spread over the entire New World, from the Arctic Ocean to Tierra del Fuego, over a period of just several thousand years.

Along the way, humans had to learn how make kayaks in the Arctic, hunt buffalo on the Great Plains, and make poison blow guns in the Amazon. It’s unlikely that human evolution occurred rapidly enough to acquire these varied skills innately in the same way that, for example, birds build nests or termites build hills.

Rather than hardwire into our genes a distinct ability for making kayaks, hunting buffalo, or fashioning poison blow guns, evolution instead encoded the general purpose skill of imitation. Given a large enough population and enough trial and error, tribe members will eventually figure out how to build a serviceable kayak, and the rest can accurately imitate the process.¹⁹

We imitate more than almost all other animal species. As soon as someone creates a useful innovation, others quickly adopt it. Yet our propensity to imitate also serves to amplify maladaptive behaviors, primary among which is mass delusions of all types, particularly the propensity of modern societies to participate in financial manias.

We are also the ape that tells stories. When our remote ancestors needed to communicate with each other to survive, they certainly did not do so with the kinds of mathematical tools used by the competent investor. The primary mode of that communication was (and still is) narration: “You go right, I’ll go left, and we’ll spear the mastodon from both sides.”

We are narrative animals, and a compelling tale, no matter how misleading, will more often than not trump facts and data. Not only do people respond more to narratives than to facts and data, but preliminary studies demonstrate that the more compelling the story, the more it erodes our critical-thinking skills.²⁰ This research also suggests an inherent conflict of interest between the suppliers and consumers of opinion. The former—maybe your stockbroker or a talking head on CNBC—wishes to convince and will devise the most compelling narratives possible, whereas the investor should intentionally avoid those narratives and rely only on data, facts, and analytical discipline.

How to Spot a Bubble

Believers in the efficient market hypothesis (EMH, described in Chapter 3) recoil at the very idea of stock bubbles. As EMH inventor Eugene Fama says, “The word ‘bubble’ drives me nuts, frankly.”²¹

The antipathy of EMH enthusiasts toward the existence of bubbles is understandable. The heart of modern finance formulates and tests mathematical models of market behavior. Isaac Newton’s lament that he could calculate the motions of the heavenly bodies but not the madness of men was likely apocryphal, but it illuminates a deeper truth. If Newton couldn’t describe a bubble in mathematical terms, then perhaps no one ever will.

Since Newton’s time, financial economists have tried to predict bubble behavior in terms of the speed and magnitude of price increases. Academic William Goetzmann, for example, found that markets that doubled in price over one year had only a 7% chance of halving in the next year, and a 17% chance over the next five years. In other words, bubbles are rare, and most frothy markets are not followed by crashes.²²

Supreme Court justice Potter Stewart approached the objective definition of a complex social phenomenon from a different direction in the case of Jacobellis v. Ohio:

Under the First and Fourteenth Amendments, criminal laws in this area are constitutionally limited to hard-core pornography. I shall not today attempt further to define the kinds of material I understand to be embraced within that shorthand description, and perhaps I could never succeed in intelligibly doing so. But I know it when I see it.²³ (italics added)

Just as Newton could not model the madness of men, and just as Fama pushes back against the word “bubble,” Stewart’s famous statement conveys that although he couldn’t linguistically model hard-core pornography, he knew what it looked like. Jacobellis v. Ohio applies equally well to bubbles. Even if we can’t model them mathematically, we surely know one when we see it.

The financial manias covered thus far—the Mississippi Company, South Sea, English Railway, and 1920s stock market—all exhibited four highly characteristic features.

First, financial speculation becomes the primary topic of everyday conversation and social interaction that sometimes even leads to public bedlam, as described by Mackay on the street outside John Law’s house: “Dukes, marquises, counts, with their duchesses, marchionesses, and countesses, waited in the streets for hours every day before Mr. Law’s door to . . . be near the temple whence the new Plutus was diffusing wealth.”²⁴

Gridlock seized the streets outside the coffeehouses where shares traded. Recorded one historian:

Throughout the length and breadth of the land, men’s minds were engrossed by the same subject. Party politics were absorbed by it. Whig and Tory left off squabbling, and Jacobites ceased to plot. At every inn, on every road, throughout the country, the talk was the same. At Aberystwith, and Berwick-on-Tweed, at Bristol and St. David’s, at Harwich and Portsmouth, at Chester and York, at Exeter and Truro—almost at the Land’s End—the talk was only of South Sea Stock—nothing but South Sea Stock!²⁵

During the 1920s, people thronged the public rooms of brokerage houses, breathlessly awaiting the posting of stock prices; Frederick Lewis Allen recalled that during the 1920s:

Stories of fortunes made overnight were on everybody’s lips. One financial commentator reported that his doctor found patients talking about the market to the exclusion of everything else and that his barber was punctuating with the hot towel more than one account of the prospects of Montgomery Ward. Wives were asking their husbands why they were so slow, why they weren’t getting in on all this, only to hear that their husbands had bought a hundred shares of American Linseed that very morning.²⁶

The 1990s saw a nearly identical obsession with stock investing; so pervasive were stories of the effortless wealth to be made from dot-com stocks that one could not attend a social gathering or enter a cab without hearing about Juniper Networks or Cisco. One of the seminal events of that era was the tumultuous initial public offering (IPO) of Netscape, which produced the first widely used internet browser. At Morgan Stanley’s Netscape desk on the company’s IPO day, August 9, 1995, traders manned over 200 workstations, at each of which simultaneously rang several extensions with a deafening cacophony of clients anxious for Netscape shares. The Grateful Dead’s Jerry Garcia died that day of a massive heart attack. Rumor has it that his last words were, “Netscape opened at what?”²⁷

The second characteristic bubble feature is that a significant number of ordinary people abandon secure, well-paying professions for full-time financial speculation. Frederick Lewis Allen described an actress who during the 1920s outfitted her Park Avenue residence as a small brokerage operation and “surrounded herself with charts, graphs, and financial reports, playing the market by telephone on an increasing scale and with increasing abandon,” while an artist “who had once been eloquent about only Gauguin laid aside his brushes to proclaim the merits of National Bellas Hess [a now-defunct mail-order house].”²⁸

During the dot-com mania, many quit their dull and steady jobs to day trade. Aspiring tycoons spent several thousand dollars on day-trading boot camps, where “trainees” typically got three days of orientation followed by a week of paper trading. The “trainers” dispensed optimism in tank-car quantities: anyone could succeed if they just followed the rules. As one trainer said, “It’s just like golf. If you’re careful about how you place your feet, how you lift the club, and follow through, you’ll stand a better chance of hitting the ball straight rather than hooking it. The same principle applies to day trading.”²⁹ As long as the markets rose, the day traders stood half a chance of succeeding, but just like the plungers in the 1920s and during the railway bubble, as soon as the sky turned dark, most got wiped out.

The third and most constant feature of any bubble is the vehemence that believers hurl at skeptics. During the late 1920s, Paul Warburg, whose family had centuries of banking experience, warned that stretched valuations and exploding margin loans had caused an “orgy of unrestrained speculation” that would not only eventually savage the speculators but “would also bring about a general depression involving the entire country.”³⁰

This prognostic bull’s-eye was met with public scorn and thinly veiled anti-Semitic slaps at Warburg. The mildest label applied was “obsolete”; angrier observers accused him of “sandbagging American prosperity.”³¹

Seventy years later, nearly the same invectives were hurled at internet bubble skeptics. I remember colleagues telling me that I didn’t understand that “the internet changes everything.” More than once I heard the five-word phrase characteristic of any modern bubble: “You just don’t get it.”

The fourth and final symptom of a bubble is the appearance of extreme predictions. The South Sea bubble featured forecasts of Spain miraculously ceding its New World trade monopoly to England. In Chapter 3, we came across Irving Fisher’s infamous October 1929 proclamation that “stocks have reached what looks like a permanently high plateau.” An even juicier example of the sort of price hyperoptimism came from the late antivirus entrepreneur John McAfee, who opined in 2017 that if Bitcoin’s price did not reach $500,000 within three years, “I’ll eat my dick on national television,” a losing bet he thankfully reneged on.³²

Am I Telling You to Time the Market?

I am definitely not telling you to time the market. In the first place, as Professor Goetzmann found, bubbles are rare, and most dramatic price increases are not followed by a precipitous decline. Rather, the most sensible approach to bubbles is to simply ignore them and to stay the course with a prudent mix of stock index funds and Treasuries (or CDs or an indexed high-quality bond fund), which will automatically mandate some selling during manias.

The same goes for the subject of the next chapter—panics and crashes—which will mandate stock purchases for the same reason. In both cases, ignore your talkative neighbors, turn off CNBC, log off from the internet, and keep a tight grip on the tiller.

CHAPTER 9 SUMMARY

Images   Since the advent of fractional reserve banking and scientific rationalism four centuries ago, waves of economic booms and busts have swept through the global financial system and exposed investors to both bubbles and panics. Moreover, we navigate space age financial markets with the brains Mother Nature endowed us in the Stone Age.

Images   The investor should be especially alert for the classic signs of a financial mania: society-wide optimistic investment narratives, a rush of lay investors into full-time trading, skepticism met by outright hostility, and predictions of investment trees that grow to the sky.

* Some financial historians credit the invention of fractional reserve banking to founding of the Swedish Riksbank in 1668, though the deposits made by the earliest English traders predate this.

CHAPTER 10

BOTTOMS

How the Rich Get Richer

In the March 29, 2013, edition of The Wall Street Journal, reporter Jonathan Cheng published a classic description of expensive bear market psychology. It featured an agreeable, attractive married physician couple, Lucie White and Mark Villa:

When stock prices collapsed in 2008, the bear market wiped out half of the savings of Lucie White and her husband, both doctors in Houston. Feeling “sucker punched,” she says, they swore off stocks and put their remaining money in a bank.¹

In April 2013, as stock prices powered above their pre-2008 levels, the couple hired a financial advisor and bought back into equities. “What really tipped our hand was to see our cash not doing anything while the S&P was going up,” says White, a 39-year-old dermatologist. “We just didn’t want to be left on the sidelines.”²

Assuming that the couple stayed in the market since then, they’ve still done well, but being out of the market between November 2008 and April 2013 would have cost them. During that four-and-a-half-year period, an investment in the S&P 500 more than doubled.

It’s easy to tut-tut the Villa/Whites’ buy-high sell-low strategy. We’re all subject to the same psychological reactions to financial markets. We’re fearful during market plunges and either euphoric or afflicted with FOMO (fear of missing out) during frothy times, depending upon how aggressively invested we are.

Villa and White’s experience describes what financial economists call the dollar-time weighted gap, the best example of which is the poor timing decisions of mutual fund investors, who on average earn an annualized return 1.0%–1.5% lower than that of the underlying funds they own.³

This dollar-time weighted gap raises a question that is not often asked. The shares that the Villa/Whites sold didn’t just disappear. Someone must have bought them from them and later someone must have sold other shares back to the Villa/Whites at great profit. Who exactly bought equities from the Villa/Whites at low prices in 2008, and who sold stocks back to them at higher prices in 2013?

The problem is that even the most authoritative researchers can’t precisely identify those “someones,” but the prime suspects are hedge funds, endowment funds, ultrawealthy private investors, and the corporations whose shares are being traded.

In this suspect list, the corporations stand out. Stock IPOs cluster during frothy, ebullient markets, and investors usually overpay for them and wind up with below-market subsequent returns. Think about what happens when a privately owned tech startup with negligible assets sells half its shares to the public at an inflated price. The old private owners now own a large amount of cash they didn’t have before, while the new public owners, who own only half the shares, usually overpay for them.⁴ (Investment bankers apply this metaphor to IPO purchasers: “The ducks are quacking. Feed them.”)

Who, then, buys shares at market bottoms? A hint is found in the 1931 diary of Benjamin Roth, an Ohio attorney, who was aware that he was living in momentous times and recorded his professional and personal observations. When his son Daniel later began to practice law, his father had him read those Depression-era notes so that he might better understand the psychological traumas their clients suffered. In 2008, in the depths of the recent global financial crisis, Benjamin’s grandson Bill Roth sent the notes to financial journalist James Ledbetter, who immediately recognized their current relevance and along with Daniel Roth published them as The Great Depression: A Diary.⁵

For the investor, easily the most resonant passage is the one from December 11, 1931, seven months before July 1932, when the Dow finally bottomed nearly 90% below its 1929 peak:

A very conservative young married man with a large family to support tells me that . . . he placed a new mortgage on [his previously paid-off house] for $5,000 and invested the proceeds in good stocks for long-term investment. I think in two or three years he will show a handsome profit. It is generally believed that good stocks and bonds can now be bought at very attractive prices. The difficulty is that no one has the cash to buy.⁶ (italics added)

Obviously, as Roth documented, somebody had the cash to buy, as did those who purchased the Villa/Whites’ stocks in 2008. In the event, Roth’s brave young man likely wasn’t representative of bear market equity buyers. J.P. Morgan is supposed to have said, “In bear markets, stocks return to their rightful owners.” Scholar, journalist, and biographer Matthew Josephson provided a variation on the Morgan quote:

[During a market panic] there are many casualties, cruel transfers of individual fortunes. Yet he who possesses even a modicum of unimpaired capital is as one who watches the sand run down in an hourglass, while fully aware that he may, at the given moment, turn the glass over and begin the process anew.⁷

Just who has the “unimpaired capital” to purchase equities from the distressed and the panicked? Society’s wealthiest, who have sufficient safe assets to meet their living expenses and have yet more left to buy stocks at the fire sale. Think a retiree or heir with a 1% burn rate or Warren Buffett, whose share of Berkshire Hathaway’s 20% position in Treasury bills alone is enough to provide for many future generations of Buffetts, or for the purposes of this book, the young person with a small investment portfolio and a secure job who understands that her job skills endow her with a large amount of unimpaired human capital.

It is simply impossible to overemphasize the value of being the owner of a large amount of Josephson’s “unimpaired capital.” Anything with a government guarantee qualifies: short-term Treasuries, CDs, FDIC-insured deposits, and even the green stuff. While cash’s interest yield may at times be paltry, its psychological return is enormous. It is an elixir of equanimity that masters the Shakespeare half of investing as manifested by our own fear and greed and in the disasters that permeate financial history, so that investing’s math half can do its thing.

In the rest of this chapter, we’ll look at what awful times look like at ground level, what brings so many to ruin during them, and how to manage your “unimpaired capital” so that the rest of your capital can enjoy the uninterrupted magic of compounding.

***

Edward Chancellor’s classic volume on booms and busts, Devil Take the Hindmost, observes that financial manias represent a collective society-wide dream of boundless wealth. The awakening produces first a wave of revulsion, then mass bankruptcy, and finally the pursuit and punishment of the manias’ promoters. He cites a letter written just after the South Sea bubble’s collapse by the poet Alexander Pope to Francis Atterbury, the Bishop of Rochester. Atterbury had warned Pope about the mania, and Pope’s letter sheepishly admits that Atterbury was right. The letter beautifully describes England’s rude arousal from its dream state:

The fate of the South-sea scheme has, much sooner than I expected, verified what you told me. Most people thought the time would come, but no man prepared for it; no man considered it would come like a thief in the night; exactly as it happens in the case of our death.⁸ (italics original)

Just as abundant credit in the early eighteenth century fed booming prices, the collapse shown in Figure 10.1 almost immediately dried up credit. John Carswell, the foremost modern historian of the eighteenth-century railroad episode, summarized the disappearance of credit that panics an entire society and seizes up its financial system in the wake of a bubble’s collapse:

FIGURE 10.1 South Sea Company share price, 1719–1722

Source data: Neal, The Rise of Financial Capitalism

A tangle of ruined credit sprawled over the country like a vast, overgrown beanstalk, withering. The gentleman in Exchange Alley who said he had bilked his cabman “on account of having been bilked himself” stands for a universal picture of default. . . . The whole system of credit which had gradually grown up with the expanding economy since the middle of the previous century had suddenly collapsed.⁹

Previously abundant cash vanishes and becomes society’s most precious commodity: think Josephson’s “unimpaired capital” and Buffett’s stash of T-bills. Suddenly deprived of credit to purchase supplies and pay employees, businesses crumble in a chain reaction that spreads to suppliers and produces mass unemployment. Eventually banks collapse in a vicious cycle of self-reinforcing credit evaporation and commercial destruction.

As Carswell alludes, the situation in 1720 England was especially dire. Its sophisticated financial system, born after the 1689 Revolution Settlement and 1694 founding of the Bank of England, was just a generation old. Many worried about a permanent plunge back into the preceding medieval poverty and civil war. This fear’s most recent incarnation was the “new normal” meme that followed the 2007–2009 financial crisis.

Minsky’s criteria for bubbles, alas, work just as well in reverse. A generalized loss of faith in the once-fashionable new technologies to cure the system’s ills combines with a liquidity contraction to produce economic catastrophe. By that point, the knowledge that recoveries follow collapses has, like the memory of preceding bubbles, also fallen victim to amnesia. Finally, investors incapable of doing the math on the way up do not miraculously acquire the ability to recognize bargains on the way down.

FIND THE PIÑATA

Financial humorist Fred Schwed observed, “The burnt customer certainly prefers to believe that he has been robbed rather than that he has been a fool on the advice of fools,” a dynamic that often plays out in the wake of a bubble’s collapse.¹⁰

In 1721, motivated not only by aggrieved constituents but also its own swindled members of Parliament (MPs), Parliament investigated the share price collapse and the massive wealth accumulated by the South Sea’s arrogant chairman, John Blunt, his colleagues, and particularly government insider and chancellor of the Exchequer John Aislabie. Parliament forced Aislabie’s resignation, sent him to the Tower, and expelled six other MPs. King George I, the recipient of company largesse in the form of low-priced shares, became the object of popular derision and barely avoided sanction.

Some spoke of jailing or even hanging the company’s directors, a fate they narrowly avoided by posting bail after a brief imprisonment. Instead, Parliament confiscated their estates to compensate the scheme’s victims; it allowed Blunt to keep £5,000 of his £187,000 in assets.¹¹

The Bubble Act, which passed at the height of the mania, had not only put a brake on further speculative enterprises but also had inadvertently helped sink South Sea. It remained on the books for more than a century. Inevitably, amnesia would work its entropic magic to allow the rekindling of the market’s animal spirits by the next century’s railroad bubbles.

***

Unlike the abrupt collapses of the twin bubbles of the previous century, the deflation of the railway company shares evolved in slow motion. The central character in the railway story was a charismatic entrepreneur named George Hudson, who during the 1830s and 1840s floated stock shares that yielded generous dividends well before his rail lines were constructed, as payouts were funded by new stock sales—what we would today call a Ponzi scheme. By the late 1840s, Hudson’s system found itself hemmed in by competing lines. In a desperate attempt to outflank the competition with further line extensions, he floated even more shares. In 1847, Parliament finally outlawed payouts from funds obtained from freshly issued shares and the game was up.¹² That same year, the Bank of England administered the coup de grace with an increase in the discount rate from 3.5% to 5.0%.

Railway shares didn’t decline as much as during the South Sea bubble or even during the great twentieth-century bear markets. Rather, the leverage inherent in their subscription purchase mechanism, in which buyers had to pony up only a fraction of the full share price, resulted in widespread devastation:

Entire families were ruined. There was scarcely an important town in England but what beheld some wretched suicide. Daughters delicately nurtured went out to seek their bread. Sons were recalled from academies, households were separated: 167homes were desecrated by emissaries of the law. There was disruption of every social tie. . . . Men who had lived comfortably and independently found themselves suddenly responsible for sums they had no means of paying. In some cases they yielded their all, and began anew; in others they left the country for the Continent, laughed at their creditors, and defied pursuit. One gentleman was served with four hundred writs. A peer similarly pressed, when offered to be relieved of all liabilities for £15,000, betook himself to his yacht, and forgot in the beauties of the Mediterranean the difficulties that had surrounded him.¹³

Unlike the twin 1720 bubbles in Paris and London, the railway mania left England with valuable infrastructure that combined with the steamship to underpin England’s nineteenth-century global military and economic dominance. The ruined railway investors had unwittingly become capitalism’s philanthropists, whose investment sacrifices benefited future generations.

The same thing would happen in the 1920s, when investors lost their nest eggs in the shares of Samuel Insull’s electric companies, which powered thousands of factories and lit millions of homes. And it happened again in the 1990s, when Gary Winnick’s Global Crossing simultaneously savaged its investors and built out a large portion of today’s undersea fiber capacity.

“Wall Street Lays an Egg”

Thus quipped the headline of the entertainment newspaper Variety in late October 1929.

First came the terror. In the waning days of summer 1929, not much was made of the Dow’s September 3 record closing price of 381 or on its subsequent 10% decline by the end of that month; over the previous decade, brief price retreats had often punctuated the steady march of new highs.

October 1929, in contrast, would be long remembered not just by financial historians, but by the general public as well. In the three trading days between Friday, October 18, and Monday, October 21, the market fell another 6%. (Back then, the market traded on Saturday.) October 21 was particularly turbulent, with the Dow falling about 3% by midday before finally recovering to a loss of just 1%. Of greater concern was the day’s record volume, which caused the ticker to run behind; anxious participants did not find out how much they had lost until 40 minutes after the close.

Wednesday, October 23, was even worse, with a 6.3% price drop. Some speculators bailed to salvage what little gains remained, while others received margin calls. The next day, “Black Thursday,” saw the market drop 11% by midday. As John Kenneth Galbraith described the scene:

Outside the Exchange in Broad Street a weird roar could be heard. A crowd gathered. Police Commissioner Grover Whalen dispatched a special police detail to Wall Street to insure the peace. More people came and waited, though apparently no one knew for what. A workman appeared atop one of the high buildings to accomplish some repairs, and the multitude assumed he was a would-be suicide and waited impatiently for him to jump.¹⁴

Among the witnesses at the exchange was none other than Winston Churchill, who in that era was remembered as the author of the disastrous Gallipoli landing and as the incompetent chancellor of the Exchequer who had contributed mightily to the debacle he observed that day from the exchange’s gallery. (He described his interactions with his Exchequer aides thusly: “If they were soldiers or generals, I would understand what they were talking about. As it is they all talk Persian.”)¹⁵

He contributed this eyewitness account:

I expected to see pandemonium; but the spectacle that met my eyes was one of surprising calm and orderliness. [The brokers] are precluded by the strongest rules from running or raising their voices unduly. So there they were, walking to and fro like a slow-motion picture of a disturbed ant heap, offering each other enormous blocks of securities at a third of their old prices and half their present value.¹⁶

Churchill’s gallery observations were the prelude to yet more drama. Around noon, Wall Street’s powers that be—Charles Mitchell, Albert Wiggin, and Thomas Lamont, leaders of, respectively, National City Bank, Chase National Bank, and the J.P. Morgan Bank, among others—met to rescue the market. They deputized the tall, charismatic de facto head of the stock exchange, Richard Whitney, to act on their behalf. He shortly strode onto the floor and made arguably the most famous stock trade in finance history, bidding 205 for 10,000 shares of U.S. Steel—well above the market price—and then made similar offers for more than a dozen other stocks. It worked; the market recovered to close off only 2%.

Whitney had saved the day, but not much more. On Black Monday, October 28, the market fell 13%, and on Black Tuesday, October 29, it fell a further 12%. The consortium that had braved the storm on October 24 decided to save their skins on October 28 and 29, leaving the market nearly 40% down from its September high.

October 1929 was just the opening act of the longest and most painful episode in American financial history. Soon after the crash, the market rebounded nicely; by early 1930, it traded at a higher level than at the beginning of 1929. Over the next two years, the Dow Jones Industrial Average fell much further, finally touching bottom at 41 on July 8, 1932, fully 89% off its 1929 high.¹⁷

Roth’s diary records the sheer despair that suffused his native Youngstown, Ohio. His dentist flabbergasted him by stopping by and requesting that he send his family in for care, even if they could not immediately pay, and described how patients with a toothache could afford only an extraction.

Roth’s saloon-keeper clients, of which he apparently had several, had been bankrupted by high-pressure stock brokers. When he asked one what he would do if he ever again had money to save, he replied with tears in his eyes that he would gratefully accept a 4%–5% return on high-quality bonds—a sentiment that he would share with the next few generations of American savers.¹⁸

What’s not much remarked upon by market historians is that the sickening decline, which took almost three years, saw many days of equally dramatic gains. For example, on October 30, the day after Black Thursday, the market rose by 12.3%—almost as much as it had fallen the previous day.

In the teeth of severe bear markets, days with abnormally large price increases occur nearly as often as abnormally large price falls. They are in fact a hallmark of such declines. The same thing happened during October 2008, when the market twice rose by more than 10%; by contrast, its worst down day over the entire 2007–2009 sequence saw a fall of less than 8%. Volatility is volatility, whether on the upside or on the downside, as seen in Figure 10.2.

FIGURE 10.2 Days on which the Dow Jones Industrial Average rose or fell by more than 5%. An often-unremarked feature of bear markets is that dramatic daily price rises are seen nearly as frequently as dramatic daily price falls.

Benjamin Graham Goes out on a Limb

The 1920s and their aftermath left Benjamin Graham deeply perplexed: How could so many have been so wrong for so long? After the market cataclysm, why should any reasonable investor ever buy stocks again? If so, what criteria should she use for her selection? The result was his manuscript written with David Dodd, Security Analysis, a dense, beautifully written brick of a book first published during the depths of the Depression.

Graham put his finger on what went wrong and how a reasonable person should approach both stocks and bonds. This book is still considered a classic and has gone through many editions since.

By the time Graham wrote Security Analysis, the investing public had almost completely abandoned stocks. Most agreed with one of the leading economists of the time, Lawrence Chamberlain, who flatly stated in his widely read book, Investment and Speculation, that only bonds were suitable for investment. A 1940 survey by the Federal Reserve Board found that 90% of the public expressed opposition to the purchase of common stocks, an attitude that would remain unchanged for a generation.

Graham, as he always did, approached things from first principles. What was investing? He wrote that an investment, upon thorough analysis, promises safety of principal and an adequate return. Investments that don’t meet these requirements are speculative.

Graham found a cornucopia of suitable stock investments in 1934. He introduced a wonderful amoral relativism to investing: there were no intrinsically “good” or “bad” stocks. At a high enough price, even the best companies were speculative. At a low enough price, even the worst companies could be a sound investment.

Graham recommended that the most conservative investors hold at least 25% of their portfolios in common stocks, and that even the most aggressive investors hold no more than 75%. The implication was that the average investor should hold a 50/50 split between stocks and bonds. Although tame by today’s standards, in the depths of the Depression, recommending any stock ownership at all was startling.

In 1932, prices were so low that the aggregate stock market yielded dividends of nearly 10%, remaining above 6% for more than a decade. Almost all stocks sold for less than their book value (the rough total value of their assets), fully one-third of all stocks sold for less than one-tenth of their book value, and a few even sold for less than their cash on hand. Stocks could scarcely be given away, even at these prices. Anyone paying good money for them was considered certifiable.

FIND THE PIÑATA: 1930s EDITION

In the wake of the 1929–1932 stock market disaster, the country’s “burnt customers” found their target in the person of Charlie Mitchell, the president of National City Bank, whose brokers had plied the institution’s trusting banking customers with dodgy bonds and speculative stocks. Mitchell described to a journalist how, when one of his young salesmen encountered a slump in client interest, he would take the neophyte to the top floor of the Bankers’ Club to survey the multitudes below. “Look down there. There are six million people with incomes that aggregate in the thousands of millions of dollars. They are just waiting for someone to come and tell them what to do with their savings. Take a good look, eat a good lunch, and then go down there and tell them.”¹⁹

Sell his brokers did, unloading securities that included an astounding $1.5 billion alone in stocks and bonds that the National City Bank’s investment arm issued, an operation so successful that it often ran out of newly issued securities to offer its customers.

Mitchell would meet his match in Ferdinand Pecora, the chief counsel of the Senate Committee on Banking and Currency. Of humble Italian-American origin, Pecora was a connoisseur of criminal behavior, and he quickly recognized that Mitchell, typical of entitled corporate thoroughbreds, saw nothing legally or ethically amiss with National City’s high-pressure tactics. All Pecora had to do was to ask the haughty bank president just how his salesmen operated. Over eight days of testimony, Pecora dismantled Mitchell by leading him methodically and politely through the moral swamp that was the National City sales apparatus.

How much did Mitchell have to pay his salesmen to induce them to sell their clients stocks and bonds? Not much, said Mitchell, only about $25,000 per year—about 30 times the typical American salary. What did the bank pay Mitchell? Over one million dollars per year, an unheard-of salary even for the highest-paid executives in that era.

There was much more, including Mitchell’s income tax evasion and the ruination of the bank’s low-level employees, who bought bank stock at inflated prices out of their paychecks and then were fired after they had finally paid off the shares. Unfortunately for prosecutors, Mitchell had not actually violated the lax securities laws of the period. But a public thirsty for legal retribution forced a trial for fraud, and Mitchell was duly acquitted on all counts.

On the positive side, four major pieces of federal legislation came out of the Pecora hearings. Unlike the post-bubble English experience, the committee’s effect on the financial system was salutary. Three of the four laws still shape our modern market structure. The Securities Act of 1933 made the issuance of stocks and bonds a more open and fair process; the Securities Act of 1934 regulated stock and bond trading and established the Securities Exchange Commission; and the Investment Company Act of 1940, passed in reaction to the investment trust debacle, allowed the development of the modern mutual fund industry. This legislative ensemble made the US securities markets the most tightly regulated in the world. If you seek an area where rigorous government oversight contributes to the public good, you need look no further than the US financial markets, the planet’s most transparent and equitable.

The fourth piece of legislation, the 1933 Glass-Steagall Act, which separated commercial and investment banking, was eroded during the post-1980s era of free market fundamentalism before its final repeal in 1999. Adding insult to injury, the global financial crisis did not see a reprise of the Pecora hearings or any prosecution of those behind the fraudulent lending practices that caused that financial and economic disaster.

Financial history, though, hasn’t ended, and it seems likely that at some future date the ghost of Ferdinand Pecora will return to wreak justice on the con men and rogues who inevitably accompany, and abet, financial manias.

***

The period between 1966 and 1982 saw the longest stretch of negative real returns in US stock market history, aggravated by high inflation wrought by successive oil crises and a Federal Reserve unwilling to tackle that inflation with the requisite interest rate hikes, an oversight spectacularly remedied by the 1979 appointment of chairman Paul Volcker.

Not all stock market crashes follow well-established bubbles. Rather, the 1960s saw a modest enthusiasm for the “Nifty Fifty,” glamorous companies with disruptive products that were seen as the can’t-miss crown jewels of American capitalism: McDonald’s, Disney, Polaroid, Hewlett-Packard, and Xerox, which typically sold at price-to-earnings (P/E) ratios approaching triple digits.

During the first years of the bear market, shares in these companies held up, but eventually they fell victim as well. The P/E of Disney fell from 76 to 11; Polaroid, from 90 to 16; and Hewlett-Packard, from 65 to 18. McDonald’s sold at a P/E of 9 as late as 1980. Down market, the damage was even worse. By the end of 1974, the average stock sold at seven times earnings, and fully one-third of those companies could be bought at cheaper than five times earnings.

“The Death of Equities”

In August 1979, BusinessWeek ran a cover story with the headline, “The Death of Equities” and few had trouble believing it. The Dow Jones Industrial Average, which had toyed with the 1,000 level in January 1973, was now trading at 875 six and a half years later. Worse, inflation was running at almost 9%. A dollar invested in the stock market in 1973 purchased just 71 cents of consumer goods, even allowing for reinvested dividends. According to the article,

The masses long ago switched from stocks to investments having higher yields and more protection from inflation. Now the pension funds—the market’s last hope—have won permission to quit stocks and bonds for real estate, futures, gold, and even diamonds. The death of equities looks like an almost permanent condition—reversible someday, but not soon.

Contrast today’s universal acceptance of equity investing with the sentiment described in the BusinessWeek article, when diamonds, gold, and real estate were all the rage. The price of the yellow metal had risen from $35 per ounce in 1968 to more than $500 in 1979 and would peak at more than $800 the following year (roughly $3,000 in today’s dollars). Still, there are similarities between the 1970s and today. Now the wise and lucky own houses in cities with desirable real estate. Back then, those who had purchased their houses for a song in the 1950s and 1960s were by 1980 sitting on real capital wealth beyond their wildest dreams. Stocks and bonds? “Paper assets,” sneered the conventional wisdom. The article continued:

At least 7 million shareholders have defected from the stock market since 1970, leaving equities more than ever the province of giant institutional investors. And now the institutions have been given the go-ahead to shift more of their money from stocks—and bonds—into other investments. If the institutions, who control the bulk of the nation’s wealth, now withdraw billions from both the stock and bond markets, the implications for the US economy could not be worse. Says Robert S. Salomon Jr., a general partner in Salomon Brothers: “We are running the risk of immobilizing a substantial portion of the world’s wealth in someone’s stamp collection.”

In the late 1960s, more than 30% of households owned stock. But by the 1970s and early 1980s, that number was only 15%.²⁰

Next, the article attacked the very idea that stocks might themselves be a wise investment:

Further, this “death of equity” can no longer be seen as something a stock market rally—however strong—will check. It has persisted for more than 10 years through market rallies, business cycles, recession, recoveries, and booms. The problem is not merely that there are 7 million fewer shareholders than there were in 1970. Younger investors, in particular, are avoiding stocks. Between 1970 and 1975, the number of investors declined in every age group but one: individuals 65 and older. While the number of investors under 65 dropped by about 25%, the number of investors over 65 jumped by more than 30%. Only the elderly who have not understood the changes in the nation’s financial markets, or who are unable to adjust to them, are sticking with stocks.

After reading this chapter and the last, you can grasp the sublime irony of this passage. Did the older people stick with stocks in 1979 because they were out of step, inattentive, or senile? Hardly—they were the only ones who still remembered how to value stocks by traditional criteria, which told them that stocks were cheap, cheap, cheap. They were the only investors with experience enough to know that severe bear markets are usually followed by powerful bull markets. A few, like my father, even remembered the depths of 1932, when our very capitalist system seemed threatened and some stocks yielded steady 10% dividends.

The BusinessWeek article ended by adding insult to injury:

Today, the old attitude of buying solid stocks as a cornerstone for one’s life savings and retirement has simply disappeared. Says a young US executive: “Have you been to an American stockholders’ meeting lately? They’re all old fogies. The stock market is just not where the action’s at.”²¹

The BusinessWeek article shows just how markets can go to extremes—a valuable lesson in and of itself—as well as a demonstration of several more salient points. First, it is human nature to be unduly influenced by the last 10 or even 20 years’ returns. It was just as hard to imagine that US stocks were a good investment in 1979 as it is to imagine that they might not be as good now.

This is doubly true for bonds. Before the bond market carnage of 2022, investors had gotten used to the nearly relentless four-decades-long fall in rates and thought of bond prices as a one-way bet. They forgot that the four decades between 1941 and 1980 saw, in Keynes’s famous phrase, “the euthanasia of the rentier.” (Rentier is an archaic term for bondholder.)

Second, when recent returns for a given asset class have been very high or very low, put your faith in the longest data series you can find—not just the most recent data. For example, if the BusinessWeek article had explored the historical record, it would have found that between 1900 and 1979, stocks had returned an inflation-adjusted 6%.

In addition, make a habit of estimating expected future returns. At the time that the article was written, stocks were yielding more than 5% and earnings were continuing to grow at a real rate of 2% per year. Anyone able to add could have calculated a 7% expected real return from these two numbers. Between the article’s publication and the end of 2022, the S&P 500 actually returned 8% after inflation, the additional 1% coming from the increase of valuations typical of recoveries from bear markets.

***

While it’s easy to imagine buying at the bottom, when the time comes you will be faced with three formidable roadblocks. First, there’s human empathy, which, at least financially, is one expensive emotion, since channeling the fear and greed of others often comes dear. The corollary to human empathy is our evolutionarily derived tendency to imitate those around us, particularly if they all seem to be getting rich with tech stocks and cryptocurrency.

My own unscientific sampling of friends and colleagues suggests that the most empathetic tend to be the worst investors. Empathy is an extraordinarily difficult quality to self-assess, and it might be worthwhile to ask your most intimate and trusted family and friends where you fit on its scale. To use a Yiddish word, the more of a mensch you are, the more likely you are to lose your critical faculties during a bubble and to lose your discipline during a bear market.

Second, there’s the “rat hole problem.” It’s impossible to know where the “bottom” really is until it’s far in the rearview mirror. Let’s say that your bear market strategy is to purchase more equities every time the S&P 500 falls by 20%. The S&P closed at 1,565 on October 9, 2007, so you would have purchased stocks at 1,253, again at 1,002, and a third time at 802 (1,002 × 0.8). Would you really have had the moxie to make that last purchase, having suffered severe losses on your first two? The S&P fell even further after that last purchase, finally bottoming on March 9, 2009, at 677.

Performing the same exercise with the Dow Jones Industrial Average from the market peak in September 1929 at 378 yielded no fewer than nine successive purchases, just barely missing a tenth one on the July 9, 1932, low of 42.

To repeat Benjamin Roth’s plaintive response to cheap stocks: “The difficulty is that no one has the cash to buy.” Or as Benjamin Graham said, “Those with the enterprise haven’t the money, and those with the money haven’t the enterprise, to buy stocks when they are cheap.”²²

Third, stocks don’t get cheap in a vacuum. Alarming narratives always accompany dramatic price declines. In both the 1930s and in 2008–2009, the entire economy seized up and appeared to be plunging off a cliff—recall Senator Burr instructing his wife to withdraw as much cash as possible from their bank.

During the 1970s, Americans saw their savings corroded on almost a daily basis by inflation. The 1979 BusinessWeek article described how only seemingly addled old folks owned stocks, and bonds were widely deemed to be “certificates of confiscation.” In March 2020, it was easy to imagine a world economy devastated by a lethal pandemic for which a vaccine seemed somewhere between distant and impossible.

Do not underestimate the courage it takes to hold stocks during the worst of times, let alone to purchase more. Holding and buying assets that everyone else is running from takes more fortitude than many investors can manage.

It helps to realize that not only are humans the apes that imitate, but we are also the apes that tell stories. Humans understand the world, first and foremost, through narratives, not data and facts. As we’ve seen in the previous two chapters, narratives often evolve into a societal contagion that can prove expensive to the unwary investor.

As the BusinessWeek article and subsequent history demonstrated, cheap stocks excite only the dispassionate, the analytical, and the long-lived. If you can manage two of those three, you should be well rewarded.

CHAPTER 10 SUMMARY

Images   The modern capitalist system, which relies on elastic credit from both private and government banks, is fundamentally unstable. Because of this, the typical investor will live through at least a few bubbles and a few panics.

Images   Markets don’t become too expensive or too cheap without good reason. Just as market manias are based on euphoric narratives, pessimistic stories suffuse market bottoms. Ignore both kinds of narratives.

Images   Adhere to the math of investing, and manage your emotions with a goodly pile of safe assets. In order to make it through the market bottoms—the main hazards on the highway of riches—you’ll need patience, cash, and courage, and in that order. Safe assets can be thought of as a concentrate of courage. Despite their low yield, in the long run the fortitude they supply make them arguably the highest-returning assets in your portfolio.

PILLAR THREE

THE PSYCHOLOGY OF INVESTING

Evolution’s Revenge

The biggest obstacle to your investment success is staring out at you from your mirror.

Our evolutionary past endowed us with behaviors that enhanced survival on the African plains and savannas, but which in the modern postindustrial present will rob you faster than an unlucky midnight turn in Central Park.

We discovered in Chapter 9 that raw brainpower alone doesn’t guarantee investment success, as demonstrated by Sir Isaac Newton. Although William Shakespeare was part owner of a theater, we have no historical record of his investment returns, but given his keen eye for human foibles, they might well have been better than Sir Isaac’s.

In Chapter 11, we identify the biggest psychological enemies of investment success. I guarantee you’ll recognize most of these as the face in the mirror. In Chapter 12, we’ll devise strategies for dealing with them.

CHAPTER 11

MISBEHAVIOR

A standard feature of basic flight instruction involves soft field operations: learning how to land on and depart from short grass landing strips.

Operating on a rough field involves keeping the aircraft’s fragile nose gear off the ground for as long as possible. The initial landing is relatively easy; the student simply keeps full back pressure on the control yoke until the nose settles down as the plane slows.

Takeoff is another matter. After applying full throttle, the instructor again has the student pull fully back on the yoke, and as the plane bumps ever more vigorously across the turf, its nose gradually rises and it finally lifts off. The student is now confronted by a rapidly approaching stand of trees at the strip’s far end—a feature intentionally chosen by the instructor.

Instinctively, in an effort to clear the trees, the student continues to pull fully back on the yoke. This is exactly the wrong thing to do, since the plane is flying too slowly to climb out of “ground effect.” At this point, the instructor says “my plane” and pushes the nose down, directly at the looming trees; the nose-down attitude allows the aircraft to rapidly gain enough speed to climb into an uneventful departure.

Training for any complex vocation or avocation, be it piloting, the law, medicine, armed service, or law enforcement, boils down to learning how to replace our instinctive responses with more effective (and occasionally more survivable) alternatives.

This is true in spades for investing. The analogy with soft field takeoffs is especially apt. When faced with a looming bear market, the best response is usually to aim straight at it.

***

As put by Benjamin Graham, “The investor’s chief problem—and even his worst enemy—is likely to be himself.”¹ Modern neuroscience describes two different brain systems behind this truism: one that mediates the fast-moving emotional responses located in our ancient limbic systems—our “reptilian brain”—and the evolutionarily more recent and slower conscious thought apparatus located in the overlying, much larger neocortex. In 2000, psychologists Keith Stanovich and Richard West labeled them System 1 and System 2, a banal taxonomy we’ve stuck with ever since.²

Until recently, economics’ major premise has been that investors are rational and act in their own self-interest. There’s just one problem: it isn’t true. Like everyone else, investors depend too much on their limbic system and not enough on their neocortex. To synthesize Graham, Stanovich, and West, our System 1 is our own worst financial enemy.

You’ve almost certainly heard the cliché about markets being in the thrall of fear and greed. These emanate from two System 1 structures, respectively, the amygdalae and nuclei accumbens. (These are both paired structures, one on each side of our brain, so I’ll refer to them in the Latin plural form. You’re more likely to see them referred to in the singular: nucleus accumbens and amygdala.)

The amygdalae lie a bit under both temples; their name derives from the Greek word for “walnut,” which they resemble. They respond to both fear and disgust, so when you are gripped with anxiety during a bear market, blame your amygdalae. Our nuclei accumbens can very roughly be thought of as our pleasure centers; more accurately, they fire in anticipation of pleasure, the financial version of which is greed.

Our reptilian System 1 dominates our analytical System 2. We usually deploy System 2 to rationalize the emotionally driven conclusions of our System 1; in psychologist Daniel Kahneman’s words, System 2 functions mainly as System 1’s press agent. This chapter describes the most costly investment behaviors that arise from System 1’s dominance. It’s likely that you suffer from all of these behavioral flaws.

***

When I wrote the first edition of this book 20 years ago, the field of behavioral economics, though a generation old by that point, still had not penetrated the public consciousness. The work of the field’s giants—Daniel Kahneman and his colleague Amos Tversky, and financial economist Richard Thaler, who shared the 2017 Nobel Prize in economics with Eugene Fama—took some explaining.

Two decades later, the work of Tversky and Kahneman has received the popular attention it deserves, especially after the latter’s publication of his bestselling Thinking, Fast and Slow. (Thaler had his pop culture moment when he and actress Selena Gomez explained the mechanics of collateralized debt obligations and the “hot hands” fallacy in the Academy Award–winning movie The Big Short.)

Nowadays it seems that everyone’s a neuroeconomist. It’s essential to identify which aspects of behaviorial economics are useful to investors and to ignore those that are not.

Before proceeding, I’ll introduce yet one more psychologist, Philip Tetlock, whose work I find at least as relevant to investors as that of Tversky, Kahneman, and Thaler. Beginning in the late 1980s, Tetlock studied the predictive abilities of authorities in diverse fields by tabulating the performance of 28,000 forecasts made by 284 experts in politics, economics, and domestic and strategic studies. How well did the experts do? Not well at all.

Tetlock found that nearly all the forecasts underperformed simple statistical rules that fed off the “base rate,” the frequency of past events. This was not a new result; Tetlock was inspired by a much earlier study by psychologist Paul Meehl, which evaluated his clinical colleagues’ ability to predict outcomes like the frequency of parole violations or pilot performance. Meehl found that the combination of the base rate and simple algorithms predicted results better than did most of his highly experienced colleagues, a finding that has since been replicated in many other fields.³ (Meteorologists forecast very well, since their forecasts receive almost immediate feedback, whereas radiologists forecast poorly because they only receive intermittent feedback.)

The implications of Tetlock and Meehl’s work to investing are obvious. Ask a “market strategist” about the likelihood of a bear market, arbitrarily defined as a decline of 20% or more, and you’ll get an erudite narrative involving Fed policy, industrial output, earnings growth, debt/GDP ratio, and so forth.

Tetlock and Meehl discovered that it’s best to ignore this sort of narrative reasoning and simply look at the historical frequency of such price falls. For example, calendar monthly declines of more than 20% have occurred in 3% of the years since 1926. This kind of base rate analysis proves more accurate in forecasting the likelihood of a crash than narrative-based expert opinion.

One type of expert performed especially miserably. Tetlock referred to this group as “hedgehogs”: ideologues who view the world through a coherent, all-encompassing theory. Think of a Marxist, a free-market libertarian, or a financial theorist who explains all price moves in terms of cycles of various lengths. A second class of experts, “foxes,” favor nuanced reasoning from multiple viewpoints; they did better than average, although they still lagged the base rate forecast.

Tetlock also tested the forecasting effect of expertise, which he divided into three levels: those of undergraduates, of recognized authorities in the area of a given forecasting question, and of “dilettantes” who were knowledgeable in one field but were forecasting outside it. Unsurprisingly, the undergraduates performed the worst, but on average the experts performed no better than the dilettantes. Specialty expertise did benefit foxes’ forecasts, but worsened those of the hedgehogs.⁴

As the saying goes, prediction is hard, especially about the future. Start with what seems like a simple problem: predicting the path of a cue ball around a billiards table. It’s easy to calculate the motion for the first few caroms, but after the sixth one, we need to consider the gravitational effect of the people around the table. Most real-life decision-making involves vastly more data and complex analysis than that required to calculate a billiard ball’s path.

In the 1970s, Kahneman and Tversky began their collaboration by studying how humans approach this overwhelming complexity. They published a landmark paper in the prestigious journal Science, in which they outlined the most basic decision-making and forecasting errors.⁵

A typical Kahneman/Tversky paradigm from this paper runs: “Steve is very shy and withdrawn, invariably helpful, but with little interest in people, or in the world of reality. A meek and tidy soul, he has a need for order and structure, and a passion for detail.” Is he a librarian or farmer? Most people would label him a librarian. Not so: there are far more farmers than librarians, and plenty of farmers are shy. Rather than think about the Steve/librarian/farmer problem quantitatively, most people go straight for a qualitative, and often incorrect, answer.⁶

Kahneman and Tversky found that we respond to the impossible complexity of real-world decisions by ignoring that complexity. Instead, we deploy heuristics: mental shortcuts that avoid the hard work of data acquisition and analysis. In their Science article, they identified three types of shortcuts:

Images   Representativeness: the substitution of facile qualitative similarities for more quantitative analysis, as in the shy Steve puzzle. Perhaps the most common financial heuristic is the great company/great stock fallacy, described in Chapter 2.

Images   Anchoring: the emphasis on the first piece of data we see, which companies and salespeople exploit with the suggested retail price, and negotiators deploy with outrageous opening offers.

Images   Availability: how compelling a narrative or event is, which determines how much credence we give it. This is by far the most important of the three, so central that Kahneman and Tversky assigned it an acronym: WYSIATI, or “what you see is all there is.” Recency is the most common form of the availability heuristic. For example, people are far more likely to purchase earthquake insurance immediately after a major temblor. Finance abounds with examples, most especially pervasive optimism/pessimism for a particular asset class following prolonged high/low returns.

WE CRAVE NARRATIVES

These heuristics go a long way toward explaining the most common investing mistakes, all three of which feed into our susceptibility to narratives. Human beings are not only the ape that imitates, but also the ape that tells stories. Our remote ancestors didn’t have sharp claws and teeth, didn’t run very fast, and couldn’t fly. Were it not for their ability to communicate with each other, we wouldn’t be here today. Further, their communication didn’t involve numerical data or mathematical formulae. Rather, they narrated about how to avoid becoming a predators’ lunch and how to become better predators themselves.

As the late Kurt Vonnegut put it, “Tiger got to hunt, Bird got to fly, Man have to ask, ‘Why, why, why?’ Tiger got to sleep, Bird got to land, Man have to say he understand.”⁷ When a problem becomes too logically or mathematically complex to grasp easily, humans default to storytelling mode that fools us into thinking we understand things that we are in reality clueless about.

For these reasons, humans prefer narratives to facts and data. As we’ve seen in the preceding chapters, that can become a very expensive proposition. The disconnect between facts and narrative sets up a conflict between those who sell opinions—in this case the investment industry—and those who consume them—in this book, investors. In general, opinion sellers should offer narratives, and opinion consumers (you and I) should ignore them and focus purely on the numbers: the Gordon equation, the basic statistics of investment classes, and the ironclad math of portfolio accumulation and spending. In the same vein, the intelligent investor tunes out stories about Fed policy, unemployment numbers, and geopolitical events, for the simple reason that if something is in the headlines, it’s already been factored into prices.

Popular finance books provide an excellent barometer of uninformed, narrative-borne public sentiment. One group of researchers found that when the bookshelves turned bearish (The Crash of 1979), stocks had above-average future returns. The opposite happened when bullish titles (Dow 36,000) lined the shelves.⁸

We Want to Be Entertained

Not only do humans like to tell stories, but they want to be amused by them as well. Until recently at least, owning shares of Netflix was much more enjoyable than owning John Deere or Procter & Gamble.

Many, if not most, of our purchases of both consumer goods and investment vehicles can be broken into two components: entertainment and investing. You can think of your dollar lottery ticket purchase as an “investment” with a one-week expected return of minus 50 percent. People buy them because their entertainment return compensates for their negative investment return and enables their purchasers to dream of spending the rest of their lives on a Maui beach with a steady supply of iced cocktails at hand.

Some investments behave the same as lottery tickets, particularly the initial public offerings (IPOs) of the stocks of glamorous tech companies. Decades of research demonstrate that IPOs combine low returns with high risk. One widely quoted paper demonstrated that in the three years following issuance, IPOs underperformed the market by a total of 27%.⁹

Even before the advent of modern econometric research, Benjamin Graham, in his seminal Security Analysis, wondered why folks bought IPOs. Here’s why: it is so much more fun to take a chance on finding the next Apple or Tesla than to own a company that makes tractors or toilet paper.*

About three decades ago, I enjoyed a dinner at the local outlet of a popular new Mexican restaurant chain. Impressed with the food and service, I researched the stock. It turned out that at the time, ethnic restaurant chains were all the rage in the equity markets, and an army of happy diners had already bid up the Mexican chain’s stock price to a triple-digit P/E, so I passed.

The more public visibility a company has and the more well-known and entertaining its story, the lower its future returns are likely to be. By contrast, the most obscure companies in the most unglamorous businesses—value companies—often have the highest returns. One of Peter Lynch’s best Magellan Fund picks was a company with an easily forgettable name in an unfashionable industry, Crown Cork & Seal.

In the famous paper “Unnatural Value: Or Art Investment as Floating Crap Game,” economist William Baumol found that paintings were, on average, lousy investments. Nonetheless, he concluded, “None of this implies that people should desist from the ownership of art works. It may well represent a very rational choice for those who derive a high rate of return in the form of aesthetic pleasure.”¹⁰ (Since the article’s publication, the prices of artwork, especially modern art, have risen dramatically along with the secular bull market of the past few decades.)

This reasoning certainly doesn’t apply to sexy companies. If it’s entertainment you want, chasing the latest IPO is likely to prove more expensive than buying out the theater for an evening’s Hamilton party and riskier than skydiving.

We Frighten Too Easily

If you have trouble staying the course during the rough patches, blame your amygdalae again. Ten thousand years ago, when they lit up with the hiss of a snake, yellow and black stripes in the peripheral vision, or the sighting of a patrol from a neighboring tribe, our amygdalae enhanced our survival. (And not just in humans: monkeys who have had their amygdalae removed lose their fear of human handlers, and amygdalae-less mice will happily play with cats.)

In the safety-conscious, postindustrial world, our amygdalae send out false alarm after false alarm: fluoride in the water, allergens in the atmosphere, killer bees heading north from Mexico, and pedophiles in pizza parlors. More important, these paired brain structures are likely to fire off at the first sign of a falling Dow and, in the process, shorten the survival of your retirement portfolio.

A series of experiments performed by a group of economists and neuroscientists at Stanford, Carnegie Mellon, and Iowa universities spoke eloquently to how badly System 1 screws up investment discipline. Their study examined how subjects performed on the following financial game: Subjects got $20 and chose whether or not to bet a buck a pop on 20 rounds of a coin flip. Each throw returned $2.50 for heads and lost $1.00 of the endowed $20 on tails.

The expected return of each flip was 25%, so the optimal strategy was to bet on every round, for an expected return over all 20 rounds of $5.00. (On average, the subject got $2.50 for each two flips played, but got to keep $2.00 of their pile for each pair not played, for a return of [$2.50 − $2.00)/$2.00] = 25%.)

One group of subjects did particularly well: patients with damage to their amygdalae and in other parts of their emotional circuitry. They bet in 84% of the rounds, whereas the neurologically intact (normal) participants bet in only 58% of the rounds. More important, the normal subjects reduced their betting frequency to 41% after a losing round, while the brain-damaged patients behaved more rationally, betting on 85% of rounds even after a losing toss. The authors concluded that damage to the brain’s emotional circuitry allowed patients to “make more advantageous decisions than normal subjects.”¹¹

The impaired investors showed a more rational response than the undamaged investors in this instance. However, it’s worth noting that betting on all 20 rounds carries a 13% chance of coming out behind the safe $20 an investor gets by not betting on all 20 rounds. This is a pretty good paradigm for investing in risky assets with a positive expected return. In fact, it’s a little odd that the experimenters automatically made the assumption that it was rational to go for the $5 risk premium on all 20 rounds in the face of a 13% chance of losing money. In truth, whether this risk/reward trade-off is indeed rational depends on how risk-averse the investor is.

This study tells us that the emotionally damaged subjects were more risk tolerant than the controls, and further that losing money didn’t impact their investment strategy, a hallmark of a disciplined investment approach.

Our fast-moving System 1 manufactures irrational fear from the markets’ normal randomness. We shouldn’t care about a bad day or a bad year in the stock market as long as it provides us with good long-term returns. Sadly, the limbic system rubs our noses in our short-term losses and pays far less attention to the biggest risk we face: not having sufficient assets to meet our long-term needs.

One of the major tenets of behavioral economics is that losses impact us emotionally about twice as much as gains; a loss of $1 approximately offsets a gain of $2. Consider that between 1896 and 2018, the Dow Jones Industrial Average rose on 51.9% percent of days and fell on 46.6% percent of days (and was “unchanged” on 1.5% of days, an artifact of calculating the index to only one or two decimal places in its first decades). If one day of losses offsets two days of gains in our psyches, then on average we will tend to feel bad about stock investing, since the number of gaining and losing days is nowhere near the 2:1 break-even ratio. Watching CNBC’s minute-by-minute market coverage only makes things worse.

Lengthening our time horizon out to a month doesn’t improve things much, with 58.2% winning months versus 41.8% losing months. Even at a yearly observation interval, with 81 winning years and 42 losing years, the win-to-loss ratio falls just short of the 2:1 emotional break-even point. Only when we check our portfolios every two years or less do we finally clear the grim psychological 2:1 hurdle.

Behavioral economists label this sort of hedonic short-termism “risk aversion myopia.” Investors behave as if their time horizons are approximately one year, which is where the two-to-one hedonic hurdle for stocks lives.¹²

We’re Too Fond of Analogies

In the simplest terms, representativeness is the triumph of stereotype over the base rate, and in finance, stereotypical thinking can cost you a lot of money.

We have already encountered one example of a financial representativeness heuristic: the good company/good stock fallacy. You would think that the stocks of glamorous growth companies would clock higher returns, but as we saw in Chapter 2, they don’t—at least not over the longer term. The shares of value companies do better, if for no other reason than they must offer a higher return to induce investors to buy them.

The representativeness heuristic also applies to the economies and stock markets of entire nations. It makes intuitive sense to favor shares in countries whose economies grow most rapidly, but the opposite is true in the real world. In Chapter 2 we also saw that, since 1993, China has had one of the world’s highest economic growth rates, at times exceeding 10% per year. Yet between January 1993 and December 2022, its stock market, as measured by the MSCI China Index, returned only 1.1% per year in US dollars—less than the US CPI of 2.4% for the period. The Asian tigers—Korea, Singapore, Malaysia, Indonesia, Taiwan, and Thailand—did a little better; since 1988 they have all had positive real returns, but still lower than the low-growth United States.

On the other hand, no major nation has seen its relative economic and geopolitical position fall farther during the twentieth century than the United Kingdom. In 1900, Britannia ruled not only the waves, but the world’s financial markets as well. In 2000, by contrast, it wouldn’t be too much of an exaggeration to label the country an open-air theme park with a nuclear deterrent. Once again, this had no effect on British equity returns, which were above the developed-nation average during the past 122 years.

Just as people overpay for the shares of glamorous companies, the same happens at the country level. In 2007, the BRIC nations, Brazil, Russia, India, and China, with red-hot economies, were all the rage among investors; since then, they’ve performed poorly. More systemic analysis confirms the China and UK anecdotes: good economies tend to have bad stock markets, and vice versa.¹³

Two additional phenomena explain why stocks in nations with hot economies tend to have poor returns. First, like people, companies die and new ones replace them. New shares are constantly sold, diluting the pool of existing shares. In many foreign countries, particularly in Asia, the rate of new share issuance is much higher than in the United States. This reduces per-share earnings and dividends and in turn erodes overall stock returns.¹⁴

Second, the regulatory apparatus in developed nations protects shareholders from rapacious management much better than governments do in developing nations, where management and controlling shareholders find it disturbingly easy to loot a company, a particularly serious problem that has taken its toll on Chinese stocks.

Beware of Eloquence

With some trepidation I’ll offer a hypothesis unsupported by anything beyond my own personal observations: an inverse correlation (or at least a zero correlation) between eloquence and forecasting ability.

Without naming names, many prominent finance academics tend to be below-average public speakers. In contrast, all the market-timing shooting stars discussed in Chapter 3 deployed sparkling rhetorical skill on their road to flameout.

I can tentatively offer two possible reasons for this putative inverse relationship between eloquence and forecasting skill. First, eloquence may allow the forecaster to obscure heuristic errors of analysis and intimidate those with opposing views. Media exposure is the second mechanism I believe connects eloquence and forecasting ability. The best answer that a well-informed and thoughtful finance authority can give to the CNBC host who asks about where the market’s headed is, after all, some version of “How the heck should I know?”

She’s unlikely to get invited back. Who does get invited back? Eloquent “boomsters and doomsters” who make extreme predictions in either direction that appeal to a show’s audience and juice the network’s advertising revenue.

These mechanisms set up a media-associated forecasting death spiral. Tetlock found that boomsters and doomsters are below-average forecasters. Moreover, excessive media exposure makes them overconfident and further corrodes their judgment, leading them to offer yet more extreme predictions. Additional media exposure and predictions attract yet bigger audiences and more broadcast invitations. Tetlock describes the resultant forecasting trifecta as follows: “The three principals—authoritative-sounding experts, the ratings-conscious media, and the attentive public—may thus be locked in a symbiotic triangle.”¹⁵

The takeaway: the next time you find yourself swayed and seduced by a silver tongue, a poor forecast may follow close behind.

WHACKED BY WYSIATI (WHAT YOU SEE IS ALL THERE IS): WHY THE RECENT PAST IS YOUR ENEMY

I wrote this book in the middle of one of the worst bond market routs in financial history. While there’s generally no avoiding losses in both stock and bond markets, it’s hard to ignore the error made by many fixed-income investors in the past few years.

Start with the “yield curve” of US Treasuries—their yields at each maturity. On June 30, 2020, at the tail end of the longest and most powerful bull market in bonds, a three-month T-bill yielded a painfully low 0.16%, while the 5-year note offered just 13 basis points more: 0.29%.

Let’s unpack what it meant to extend the Treasury maturity from three months to five years to get that 0.13% of extra yield. Over nearly the past century, the 5-year note has had a standard deviation (SD), that is, volatility, of 4.3% per year. In mid-2020, an investor got 0.13% more yield by taking 4.3% of risk, or 0.03% more return for each 1% of extra risk taken.*

Let’s see just how miserly a reward that 0.03% of return for each 1% of risk is by shifting gears to equities. If we assume that the equity risk premium is about 4% and stocks have an annualized SD of 16%, then equities offer roughly 0.25% of return per 1% of risk taken. That 0.25%/1% return/risk ratio provides a handy rule of thumb for deciding how much risk to take on the bond side by extending maturity. Figure 11.1 plots the yield curve in mid-2020.

FIGURE 11.1 Treasury yield curve on June 30, 2020

Extending maturity in search of yield in mid-2020 was clearly a fool’s errand and recalled financial analyst Raymond DeVoe Jr.’s famous maxim that “more money has been lost reaching for yield than at the point of a gun.”¹⁶

As I’m editing this chapter in March 2023, the yield curve is “inverted,” offering a peak return of about 5% at six months. Does this mean it’s now unwise to extend maturities beyond this, as was the case in mid-2020? Not necessarily, since in 2023 the much higher yield offers a generous cushion against loss, a cushion that was nonexistent in mid-2020, when interest rates were at the lowest point since they were first recorded five millennia ago.

I took this short detour into bond maturity because it provides a vivid demonstration of the treacherous power of recency. By 2020 bond yields had fallen more or less continuously for four decades, and many investors simply could not envision a dramatic rate rise, let alone a repeat of Keynes’ “euthanasia of the rentier.”

While the 10 years between 1999 and 2008 saw the worst 10-year stock return in US market history, the dramatic market recovery, which saw prices increase sevenfold off the 2009 low by 2021, had also erased the memory of painful losses in the equity markets and of the 17-year history of negative inflation-adjusted stock returns nearly two generations ago—just in time for 2022’s carnage in both stocks and bonds.

MATH BOX

Bond Duration

You may have read about bond duration and wondered how it relates to maturity. Duration can be thought of as the effective maturity, calculated from the present value of all coupon and principal payments, which consequently is always shorter than the actual maturity because of the coupons received before the maturity date. The higher the yield, the larger the gap between the two.

Duration, though, has a far more useful market definition, which is the ratio between changes in bond price and changes in yield.

The 5-year note’s duration in mid-2020 was very close to 5 years because of its minimal yield. During the first four months of 2022, the 5-year Treasury yield rose by 1.66%, and so its price fell by about 8%. Ouch!

A 1.66% rate rise over just four months is a rare event, and the odds of it happening at any point in time are small. Still, even if rates had stayed the same or fallen, the decision to buy Treasuries of more than a few months’ duration in mid-2020 made little sense from a risk/reward standpoint, especially given the near nonexistent coupon cushion at that point.

More WYSIATI: The Stationarity Illusion

Probably the most popular download in all of finance is Robert Shiller’s continuously updated stock market spreadsheet. His file calculates and plots his favored valuation metric, the cyclically adjusted P/E ratio, or CAPE: the current price of the S&P 500 divided by the 10-year average of its inflation-adjusted earnings. For example, at year-end 2021, it stood at 38.3, not too far off its all-time high of 44.2 at the end of 1999, near the peak of the dot-com bubble, plotted in the below Figure 11.2.

FIGURE 11.2 Shiller cyclically adjusted P/E ratio (CAPE) peaks and troughs

Source data: Shiller CAPE data file

This sort of analysis has been tempting investors ever since aggregate market data became available. What could be simpler? Buy when the CAPE, or whatever valuation metric you favor—the trailing 12-month P/E ratio, dividend yield, price/cash flow, or what have you—approaches historically low levels, and sell when it reaches historically high levels. For the CAPE, those levels might be 10 and 35, respectively.

Plotting the forward 10-year returns versus CAPE, as shown in Figure 11.3, seems to confirm this intuition.

FIGURE 11.3 Shiller CAPE versus subsequent 10-year annualized returns

Source data: Shiller CAPE data file and Dimensional Fund Advisors

Of course, there’s a catch to this surefire way to beat the market. It suffers from the “stationarity fallacy,” a subtle form of WYSIATI/recency: the assumption that not only will the future values of the CAPE look like the prior ones, but also that the relationship between current and future CAPE returns will remain the same. Imagine a bottle containing all of the stock market’s past returns and CAPE values. If the stock market is a stationary system, all of the market’s future values will fit inside the bottle’s walls. Lamentably, in the real world they leak out onto the table.

Airfoils and electrical circuits will behave the same way under the same conditions, but stocks and bonds most certainly do not, a problem that often catches out the physics and engineering types attracted to finance. If the peak of your skill set centers on phase diagrams, and you can solve differential equations as easily as you brush your teeth, it’s all too tempting to focus on the math of investing and not on its Shakespeare, as happened at Long-Term Capital Management. Call it “the engineer’s mistake.”

Before about 1955, every time the dividend yield of the stock market dipped below 4%, it suffered a serious decline. In that year, the sustained secular rise in stock prices again drove the yield below 4%, and thereafter the “sell at 4%” rule kept investors out of the market more than 90% of the time between 1955 and 1985, and 100% of the time after 1985. When the market bottomed in March 2009, the S&P 500 still yielded only 3.6%.

Recall the experience of the young Eugene Fama, who found multiple trading rules that worked well in the data set he was given by Professor Ernst, but not in the sample Ernst withheld. Researchers Elroy Dimson, Paul Marsh, and Mike Staunton (DMS) demonstrated much the same thing in the world’s stock markets in their 2013 yearbook for Credit Suisse.

For each of the 20 nations dating back to 1900 and for three global/regional indices, DMS generated trading strategies at the end of each year based on their dividend yield. They then examined how those strategies did over the next 5 years, performing thousands of trial runs over the entire 113-year period.

On average, devising trading strategies based on prior valuations added nothing going forward. The authors drolly concluded that “we learn far less from valuation ratios about how to make profits in the future than about how we might have profited in the past.”¹⁷

THE LAKE WOBEGON MIND

Sixty-four percent of Americans think they’re going to heaven, whereas only half a percent plan on traveling in the opposite direction.¹⁸

A study of business startups found that more than two-thirds of them failed within four years, and yet their founders estimated the overall success rate of businesses like theirs at around 50/50 and their own chances of success at around 70%. Fully one-third of entrepreneurs, in fact, were 100% certain that they’d succeed. The study’s authors sternly recommended that fledgling businesspeople “form relationships with outsiders who can provide objective assessments.”¹⁹

For many years, behavioral economist Terry Odean handed out a questionnaire to his Berkeley MBA class about their driving ability relative to their classmates. Typically, one-quarter of them rated themselves in the top 10% of drivers, and nearly all rated themselves as above average. Both of these estimates, of course, are mathematically impossible.

Odean once asked one of the few students who rated herself below average why she did so. She answered that she was going to rate herself in the top quarter, but then remembered that during the prior 12 months she had been cited for speeding three times, been in two accidents, and was about to have her license revoked. Only once did a student rate himself in the bottom 10 percent: a foreign student who didn’t drive.²⁰

In the same way, both individuals and professionals overestimate their financial prowess. Nearly a quarter century ago, Wall Street Journal writer Greg Ip wrote a classic article that beautifully described how both recency and overconfidence combine to distort investor expectations.

In the summer of 1998, stock markets reeled as sovereign bonds around the world fell into default—the same crisis that nailed Long-Term Capital Management. Ip examined the change in investor attitudes following the market decline and tabulated changes in investor expectations:

Remarkably, the average small investor thought that the fall in prices heralded lower future returns, never mind that the lower the price paid for any asset class, the higher its future return (or at least the lower the loss).

What’s equally remarkable about this table is that the average investor thought he’d beat the market by about 2%. Since the average investor gets the market return minus expenses and transaction costs, he will in fact get less than the market return.

THE MOST DANGEROUS OVERCONFIDENCE OF ALL

If overconfidence about financial ability corrodes returns, that goes double for overconfidence about risk tolerance. This book’s 2002 edition offered the following guide to stock/bond allocation as a function of how much the reader could tolerate the following portfolio losses:

I neglected to ask whether readers had actually ever lost 15%, 25%, or 35% of their portfolio. Simply looking at this table or running a portfolio simulation on a spreadsheet is not the same thing as facing real-world losses. The stock market only rarely falls for no good reason—bear markets are almost always the result of incipient financial system collapse, hyperinflation, or the possibility of nuclear annihilation. The fear of real geopolitical and economic catastrophe makes such times the most dangerous mountain passes on the highway of riches.

Another aspect of the disconnect between perceived and actual risk tolerance is our evolutionarily adaptive tendency to erase physical and psychological pain. We remember the joys of our decade-ago Italian vacation, but downplay the bumpy flight there, the bout of food poisoning, and the loquacious Peoria dentist on the Vatican tour. The financial equivalent of this is mentally buffing up how easily you sailed through the 2008–2009 stock market, whose considerable agita you’ve conveniently forgotten.

A HEDGE FUND IS THE INVESTMENT WORLD’S BIRKIN BAG

At the risk of pushing this book’s primate metaphors too far, humankind is not only the ape that imitates and tells stories. It’s also the ape that seeks status.

In an environment with scarce food and resources, only the most capable survive and reproduce, and the human pecking order signals genetic fitness to prospective mates. While the connection between status and the ability to find a mate has become attenuated in the modern world, humans haven’t escaped the evolutionary drive to be able to seek and acquire status. In the words of Karl Marx:

A house may be large or small; as long as the surrounding houses are equally small it satisfies all social demands for a dwelling. If a palace rises besides the little house, the little house shrinks into a hut.²¹

An old joke defines envy in different cultures. In the United States, it’s your neighbor’s bigger car; in England, your neighbor’s having tea with the Queen; in France, your neighbor’s attractive lover; and in Russia, wishing your neighbor’s cow was dead.

The investment world’s version of this joke is envy of your neighbor’ glamorous stock or hedge fund. Unfortunately, lusting after glamorous investments can damage your finances at least as much as hankering after a tony house, car, or lover.

Wealthy people often impair their medical care by fragmenting it with doctor shopping, at the extreme winding up with charlatan celebrity physicians. The same is true in finance, where the wealthy often have access to managers and investment vehicles not available to plain folks, particularly hedge funds, limited partnerships, and in the worst case, con artists such as Bernie Madoff, much of whose appeal rested on his habit of turning down prospective clients.

The investment world’s version of the celebrity physician and Birkin bag is the hedge fund, which until recently charged “two and twenty”: a 2% management fee and 20% of returns. If your hedge fund made 10% per year, fees alone totaled 4%. That’s just for starters, since these funds also incur significant transactional costs and are usually packaged through advisors and/or “funds of funds,” both of which charge yet another layer of fees. By the time all is said and done, the typical hedge fund investor flies into a headwind of about 7% per year, a handicap that not even Warren Buffett can overcome.

Hedge funds also suffer from the same “crowded trade” phenomenon that troubles commodities futures funds. The more assets that are thrown at a given asset, the higher its price and the lower its future returns.

In 2000, Yale endowment manager David Swensen wrote a brilliant, influential book, Pioneering Portfolio Management, in which he proposed a portfolio strategy radically different from the conventional 60/40 stock/bond institutional model.

He deployed less than half his portfolio in conventional publicly traded foreign and domestic stocks and bonds, and invested the rest in hedge funds, private equity, private real estate, and commodities futures.

His strategy worked brilliantly. In the 20 years between July 1987 and June 2007, he clocked a 15.6% annualized return, 4.8% higher than the S&P 500. Better yet, along the way, the endowment experienced considerably less volatility than more conventional portfolios. Good news traveled fast. By 1997, the Princeton, Harvard, and Stanford endowments had copied Yale’s trajectory into the alternatives universe.

Most good investment ideas eventually get run into the ground. By the mid-2000s, tout le monde had adopted the Yale model. As of mid-2011, the 823 large endowments tracked by the National Association of College and University Business Officers invested an average of 53% of their funds in alternative investments.

That didn’t work out well. Over the 10 years ending mid-2011, the university endowments (on average) barely nudged out the returns they could have had from a simple 60/40 mix of S&P 500/Barclays Aggregate Bond or the Vanguard Balanced Index Fund, which mimics this mix.²²

Things got worse from there. As more money crowded into the alternatives arena, university endowments fell even further behind. For the 20-year period ending June 30, 2021, the average endowment fund returned 6.8%, versus 7.5% for a standard 60/40 mix of global stock and bond indices.*

The same thing happened to hedge funds. Between 1998 and 2012, hedge fund assets grew from $300 billion to $3 trillion. One rough estimate of the “alpha,” or excess returns, available to hedge fund managers is on the order of $30 billion. A quarter century ago, in 1998, this represented 10% of the $300 billion hedge funds managed, which more than covered their fees and expenses. But that $30 billion provided only a 1% boost to the $3 trillion under management in 2012, which, after fees, put their clients seriously under water.

Figure 11.4 plots the trailing 5-year performance of the HFR global index of hedge funds against a 25/75 mix of US stocks and T-bills. This mix almost exactly reproduces the behavior of the index, except for one feature: the curve for hedge fund performance is tilted upper-left to lower-right as the hedge funds, bloated by a factor of 10 between 1998 and 2012, outperformed during the earliest years, and then underperformed as they grew elephantine.

FIGURE 11.4 What happens to hedge fund performance when their assets increase from $300 billion to $3 trillion

Source data: Hedge Fund Research and Dimensional Fund Advisors

It shouldn’t surprise, then, that hedge fund survival resembles that of pet guinea pigs; of 600 funds registered in 1996, just one-quarter still operated eight years later.²³

CHAPTER 11 SUMMARY

We all believe that we’re Mr. Spock, but in reality we’re George Costanza. (More accurately, we mistakenly believe that everyone else but us is George.) As Pogo cartoonist Walt Kelly said, “We have met the enemy, and he is us.”

Get over it—no matter how hard we try, we’re all hopelessly human.

Images   We are the hostages of our evolutionarily ancient System 1—our reptile brains—that overemphasizes the short-term risks that imperiled our survival eons ago, but ignores the longer-term risks that dominate modern life.

Images   We oversimplify the unforecastable real world with simple heuristic narratives that come nowhere near capturing the mind-boggling complexity of everyday decision-making.

Images   We seek entertainment and status on a financial playing field that penalizes both and instead rewards constant, plodding discipline.

Images   We overemphasize recent, salient events and ignore the critical “base rate” that makes the more remote past equally relevant.

Images   We overestimate our own ability, our prospects for success, and most important of all, our ability to deal with risk on those rare but critical times when it stares us directly in the face.

In Chapter 12 we’ll explore strategies for dealing with our costly financial humanity.

* Strictly speaking, when you purchase a company’s shares, you’re usually not investing in the company itself. Rather, your money goes to the shares’ previous owners. The purchase of an IPO, on the other hand, does impart the warm glow of investing in the real economy, which comes at the cost of low returns.

* Those with formal finance training will notice that the described ratio of return to risk is nearly identical to the Sharpe ratio, formally defined as (Portfolio Return − Risk-Free Return)/(SD of [Portfolio Return − Risk-Free Return]).

* A 42/18/40 mix of S&P 500/World ex-US/Bloomberg aggregate bond indexes.

CHAPTER 12

DEALING WITH THE SHAKESPEARE

As the principals of Long-Term Capital Management so woefully demonstrated, mastering the math isn’t enough. Investors must also master their own irrationality. This book’s first two sections dealt with the math of investing, and the previous three chapters described the Shakespeare of investing—those parts of human nature that can bring an investor to grief in the same way they did Hamlet, Lear, and Lady Macbeth. This chapter will cover the tools you need to combat the most insidious and egoistic Shakespeare of all—the one staring back at you in the mirror.

COMBATING WYSIATI (WHAT YOU SEE IS ALL THERE IS)

Every decade or so, the term “junk bonds” morphs from an asset class description into a popular epithet, most often spat out by someone who has just fallen victim to DeVoe’s dictum about the danger of chasing yield.

This is not a new phenomenon. Nearly a century ago, Benjamin Graham warned that the bonds of lower-rated companies should never be bought at par (their full face value), but could sometimes be profitably purchased at lower prices and higher yields.

The experience of the past several decades confirms the wisdom of his advice. During the 1990s’ savings and loan crisis, junk bonds lost 21% of their total return; during 2007–2008, 40%; and briefly with the onset of Covid in 2020, about 22%. The result: a market revulsion that, as inevitably happens, turned junk bonds into a pariah investment.*

Unlike the expected equity risk premium, which is opaque, junk bonds’ expected risk premium is plainly visible. The “junk-treasury spread” (JTS) is the difference between junk bond and Treasury yields; the actual return premium is the JTS minus the loss rate. (When companies go bankrupt, bondholders often recover some of their losses by seizing the company’s assets. The loss rate is the percentage of defaulted interest and principal after the recovery of seized assets, historically about 4% per year for a portfolio of junk bonds.)

Typically, the JTS averages about 5%, although during most of the past few decades, it’s been closer to 4%. This yield premium over safe Treasuries is only slightly larger than their 4% historical loss rate. If the junk bond holder earns 5% more in interest over Treasuries but loses 4% of it to bankruptcies, this leaves the bondholder with just 1% extra return, which comes at the price of not infrequent, jaw-dropping losses.†

During market turbulence, the JTS increases dramatically. During the 1990 and 2020 episodes, it leaped to around 10%. In late 2008, it jumped nearly to 20%. During those three occasions, Benjamin Graham would probably have approved of purchasing junk bonds, since a JTS of 10%–20% is far greater than the historical 4% loss rate. Consequently, like prestiti buyers in 1379 and stock buyers in 1932 and 2009, junk bond purchasers in 1990, 2008, and 2020 made out well.

I don’t want you to time the junk bond market, but rather to understand a more general point: the highest returns for an asset class usually occur when it becomes an object of popular revulsion.

During the late 1990s, a national media outlet quoted me pointing out REITs’ high yields and thus high expected returns. A few days later, an acquaintance called to say, “I’ve done nothing but lose money in REITs!” and hung up; I too, of course, had lost money in REITs. As a consequence of that asset class’s poor recent performance, its expected returns had risen. The rational response was to interpret the resultant disappointment and disgust as a signal to purchase more of the asset class, or at least not sell one’s existing holdings.

In order to deploy the sort of investing rationality that buys when the popular mood screams “sell,” recognize that the popular mood—the population-wide System 1—is a social force that wants to make you poor. The rational investor treats the popular mood about an asset class in the same way he’d respond to a loudmouth uncle renowned for his constant stream of misguided opinions and bad advice. The same goes double for one’s own System 1 signals.

Keep in mind that the most treacherous mountain passes on the highway of riches are our System 1 responses to the long periods of negative real stock and bond returns. It’s a near certainty that during your investing career, you’ll encounter one or two of these deep valleys in returns, which can last more than a decade. John Templeton put it best:

Bull markets are born on pessimism, grow on skepticism, mature on optimism, and die on euphoria. The time of maximum pessimism is the best time to buy, and the time of maximum optimism is the best time to sell.¹ (italics added)

Prolonged bear markets generate a revulsion against stock ownership in the population’s collective System 1, and most likely in yours as well. It screams, “Sell!” There’s nothing you can do that will directly reverse the sick feeling you get in the pit of your stomach from opening your brokerage statement at such times.

But you can cope. Here are some strategies to help you do so. First, train your System 2’s inner Spock to properly interpret your System 1’s distress. Train yourself to recognize Templeton’s “time of maximum pessimism” as a predictor of higher returns ahead and then deploy your math skills and the Gordon equation to confirm that conclusion. Over the years, I’ve learned that my most profitable purchases were accompanied by palpable nausea. As Templeton also noted, the opposite goes for the comfort and euphoria System 1 generates during financial manias, which should serve as your System 1’s way of signaling to your System 2 not to get swept up in the popular enthusiasm for risky assets.

Finally, constantly remind yourself of two things. The first is that purchasing the past 5 or 10 years’ best-performing asset classes invariably reflects the conventional wisdom, which is usually wrong. The second is that, more times than not, the purchase of last decade’s worst-performing asset class is a better idea.

Eloquence and Compelling Narratives Are Alarm Bells

Constantly remind yourself that humankind is the ape that tells stories, and for very good reason: they’re far more persuasive than facts and data. When you hear someone selling an opinion, you should first and foremost consider Tetlock’s base rate and run the numbers—the Gordon equation, the bond yield curve, and historical asset returns and risks. The optimal strategy for the sellers of opinions—in this case, investment industry shills—is to offer compelling narratives, but as an investor, you are a consumer of opinions who should avoid narratives at all costs.

Even the most educated among us—especially the most educated—revere eloquence and rhetorical skill. How often have you heard someone exclaim, “I love listening to X. She’s such a smart lady!” The connection between persuasiveness and forecasting accuracy is an object of Tetlock’s ongoing research. He suspects a negative correlation, since media outlets seek out eloquent “boomsters and doomsters,” in Tetlock’s terminology, who his studies show forecast poorly.² This has been my experience as well.

Nowhere is the negative correlation between eloquence and forecasting more evident than in finance. All of the shooting stars mentioned in Chapter 3—Joseph Granville, Elaine Garzarelli, and Nouriel Roubini—lit up a room with their wit and wisdom. As previously described, media outlets are especially attracted to eloquence and extreme predictions, which in combination provide reliable markers for poor forecasting.

Clinical psychologists and psychiatrists have long known that charm and eloquence are features of psychopathy. One of psychopathy’s primary manifestations is persuasive self-confidence, which is advantageous in the corporate environment. The disorder is more common in the executive suite than in the general population, especially in finance.

The corner office can be an expensive and dangerous place for the psychopath to wind up.³ Business history is replete with charismatic entrepreneurs who took their investors to the cleaners. In the early twentieth century, Samuel Insull built much of the nation’s power grid but also massively defrauded his shareholders. GE’s Jack Welch fiddled with the company’s earnings so they appeared to be growing reliably when in fact they were not. WeWork’s megalomaniacal Adam Neumann famously had the company pay him $5.9 million for the trademark on the word “We.”⁴ When the wise investor encounters fawning media coverage of charismatic CEOs, she hears alarm bells.

As always, the proper response to financial manias is to train your System 2 to put your System 1 on a leash. Push back when your reptile brain responds approvingly to someone with perfect diction and a narrative flair. TED Talks, with their eloquent gesticulating speakers, amplify our misleading System 1 responses with their audiences of nodding heads, clapping hands, and knowing laughs. If a presenter looks and sounds like he belongs on a TED stage, be especially on your guard.

Great Companies Are Not Great Stocks

Chapter 11 covered the most common heuristics—deceptive simplifying mental shortcuts—that can cause analytical mischief. The classic financial heuristic is the great company/great stock fallacy. Financial history and research teach that the dullest companies tend to have the highest returns. In the real world, superior growth is an illusion that evaporates faster than you can say “earnings surprise,” and the odds of your picking winning stocks from the overwhelming majority of highfliers that will soon enough flop are low.

Instead, it’s wise simply to own the overall market, on the theory that if you want to find all the winning needles in the haystack, you need to own the whole haystack. Alternatively, you might consider overweighting value stocks in your portfolio with one of the widely diversified passive value funds we’ll cover in the book’s final section. At a minimum, beware the siren song of the growth stock, particularly when people begin talking about a “new era” in investing. To again quote Harry Truman, “the only thing new in the world is the history you don’t know.”⁵

Make It Mundane

As we found out in the last chapter, entertainment often comes at ruinous expense in the investing world. In few other fields is the correlation between the sizzle and the steak so negative. If it’s entertainment you want, extreme sports and luxury cruises are likely to prove cheaper than hedge funds, private real estate, commodities futures, and celebrity money managers.

The moment you find yourself entertained by your investments, or those of your friends and family, be on your guard. A successful investment strategy should be boring. Glamorous and exciting investments tend to be “over owned” and on the receiving end of excessive amounts of capital, which drives down future returns.

The strategy most likely to make you instantly rich is to get lucky with a Powerball ticket, the investing equivalent of which is finding the next Amazon, Facebook, or Tesla. Just as with purchasing a large number of lottery tickets, a portfolio of IPOs and hot tech stocks is far more likely to leave you with subpar returns than to hit the jackpot. While it’s true that chasing IPOs and exciting tech stocks offers you the best chance of striking it rich, it also makes dying poor more likely. Tell yourself every day that the object of investing is not to maximize the odds of getting rich, but to minimize the odds of dying poor, and that the best way to do that is through a dull, low-cost, passive approach to equities wrapped in the peace of mind provided by a thick security blanket of securities backed by Uncle Sam’s full faith and credit.

Relish the Random

Realize that almost all apparent stock market patterns are just coincidence. If you dredge through enough data, you will find an abundance of stock selection criteria and market timing rules that would have made you wealthy. However, as Eugene Fama found out while an undergraduate, unless you possess a time machine, they are of no use. The experienced investor quickly learns not to optimize the past, since most market behavior is random and what worked yesterday rarely works tomorrow.

Accept the fact that stock market patterns are a chimera, just like the man in the moon or the face of your Aunt Tillie in the clouds scudding overhead. Ignore them. When it comes to financial markets, the safest and most profitable assumption is that there are no patterns. While there are a few statistical predictors of stock and market returns, these are too weak to be of any practical use.

The sooner you realize that no system, guru, or pattern will benefit you, the better off you will be. Ignore market strategists who use financial and economic data to forecast market direction. If we have learned anything over the past 90 years from the likes of Cowles, Fama, Graham, and Harvey, it’s that this is a fool’s errand. The market strategist’s job is to make your local palm reader look good.

Get Your Risks Straight

Myopic risk aversion—our tendency to focus on short-term losses—is System 1’s way of making you poor. An apocryphal story has an investor placing $10,000 in a mutual fund in the mid-1970s and then absent-mindedly forgetting about it. Shocked by the October 19, 1987, market crash, she panics and calls the fund company to inquire about the state of her account. “I’m sorry madam, but the value of your fund holdings has fallen to $179,623.”

Your System 1 equates risk with losing money right now: this year, this month, this week, or today. This instantaneous definition of risk served us well when the major perils involved neighboring tribes, deadly predators, virulent diseases, and poisonous plants, but it is ill suited to a financial environment where the major risk is failing to accumulate enough assets and to spend them wisely over an investing career lasting half a century.

Chapter 2 closed with a discussion of the actual market risks that imperil your future consumption, the four horsemen of “deep risk”: inflation, confiscation, devastation, and deflation. Yet our System 1 laser focuses us on the myopic, short-term risks of market declines that almost always turn out to be temporary.

Combating this myopic risk aversion is the most difficult emotional task facing any investor. I know of only two ways of doing this. The first is to check on your portfolios as infrequently as possible. Behavioral finance academics have found that in both the research lab and in the real world, investors who never look at their portfolios earn higher returns than those who examine their holdings frequently. (Though you should check statements once or twice per year to ensure against fraud.) Think about your house. It’s a good thing that even Zillow.com can’t offer you an accurate daily quote on its market value.

Graham observed this effect when he noted that during the Depression, investors in obscure mortgage bonds that were not quoted in the newspaper held on to them. They eventually did well because they did not have to face their losses on a regular basis in the financial pages. On the other hand, the owners of corporate bonds, which had lost less actual value than the mortgage bonds but that were frequently quoted, were more likely to panic and sell out.

The other way to avoid myopic risk aversion is a nice pile of safe assets, such as Treasuries, CDs, and high-quality money market funds, which impart priceless equanimity about market falls.

How much in safe assets should you hold? That depends on your age. The newly retired person, for example, should have at least five years of residual living expenses—funds required after receipt of Social Security and pensions—squirreled away in safe assets. Ten years is better, and even twenty years isn’t too much.

On the other hand, the young person owns a large “bond” in the form of decades of future earnings. How much she should have in safe assets depends on two things. The first factor is the security of her employment. Is she a teacher or does she work in a tech startup? The teacher should have an emergency fund to tide her over for several months, whereas the tech worker needs a bigger one. Needless to say, unless she’s an heiress, she should carry disability insurance, and if she has dependents, life insurance as well.

No matter what the investor’s age or profession, she knows that the visceral reaction to short-term losses is System 1’s way of making her poor. She learns to turn bear markets to her advantage by telling herself each time her portfolio gets hit that low prices mean higher future returns, and she further reminds herself that she isn’t going to need her stock assets for many years, if not decades.

Don’t Become a Whale

Wealthy investors are the cash cows of the investment industry, and most of the exclusive investment vehicles available to them, such as separate accounts, hedge funds, limited partnerships, private equity, and venture capital, are designed to bleed them for commissions, transactional costs, and other fees. Brokers eagerly court “whales” with impressive descriptions of sophisticated research, trading, and tax strategies, to say nothing of fancy restaurant meals and skybox seats. Don’t be fooled. Remember that the largest investment pools in the nation—pension funds and endowments—can’t beat the market. The investor with $10 million or even $1 billion probably won’t beat the market, either.

A diversified portfolio of indexed mutual funds or ETFs may not be exclusive or exciting enough for your tastes, but it’s highly likely to earn returns higher than those of your high-rent-district neighbors.

Don’t Let It Go to Your Head

The first step in avoiding overconfidence is to learn to recognize it. Do you think that you have above-average driving ability, social skills, and physical good looks? You likely don’t. If you believe that your stock-picking prowess will let you beat the market, ask yourself if you really are smarter than the folks on the other side of your trades. Of course you can’t know exactly who they are, but it’s a good bet that they’re savvy professionals whose motivations, skills, and resources far exceed yours.

Or maybe you think that you can successfully pick market-beating money managers. I hope that the data in Chapter 3 on fund performance has convinced you otherwise. If you could actually do that, you would have a lucrative career as a pension fund consultant. The nation’s largest corporations would pay you handsomely to identify superior money managers to shepherd their employees’ retirement assets.

You avoid overconfidence by constantly reminding yourself, “The market is much smarter than I will ever be. Millions of other investors are much better equipped than me, and all are searching for the financial Fountain of Youth. My chances of being the first to find it are not that good. If I can’t beat the market, the very best I can hope to do is to join it as inexpensively and efficiently as possible.”

The most liberating aspect of an indexed approach is earning the market return, which outperforms the majority of investment professionals engaged in the expensive and Sisyphean task of trying to exceed it.

CHAPTER 12 SUMMARY

Images   Ignore the past decade’s asset class returns. Focus instead on the “base rate”: the longest available series of stock and bond returns.

Images   Beware the silver-tongued guru. Eloquence and persuasiveness are often markers for poor forecasting. Fools listen to stories; the wise crunch the numbers.

Images   Be especially skeptical of “great” companies, charismatic CEOs, and the invocation of the pluses and minuses of national economies.

Images   Ignore the sizzle and go for the steak. Competent investing should be deadly dull. If you find your portfolio entertaining, there’s likely something wrong with it.

Images   Understand that short-term losses, even the most severe ones, don’t represent true financial risk, which is the result of macroeconomic and geopolitical forces well beyond your control. I advise a prudent portfolio of global stocks and short-term high-quality fixed-income vehicles.

Images   Don’t let your prosperous friends’ fancy, “exclusive” investment vehicles turn your head. They’re designed to make their brokers wealthy—not their investors.

Images   Remember that you’re not as good an investor as you think you are. The person on the other side of your stock trades isn’t a dentist from Paducah, but rather someone with fearsome capabilities, information, and resources. The safest way to avoid having that person decimate your portfolio is to buy and hold the market.

* For 1990 and 2006–2008, monthly figures for the Bloomberg High-Yield Bond Index, and for March 2020, daily adjusted prices for the Fidelity High-Income Fund.

† I’m indebted to Martin Fridson for email discussions of this issue.

PILLAR FOUR

The Business of Investing

The Carny Barkers

This book’s first edition featured chapters on the brokerage industry, the mutual fund industry, and the financial press. The message of the first and last chapters was simple: stay far, far away from any full-service brokerage or a broker, and completely ignore the financial media, both of which aim to make you uninformed and poor.

This left the investor to deal with the second arena: the mutual fund industry, at least 90% of whose products were financial toxic sludge. These high-cost actively managed funds underperformed the market with near clockwork regularity. In 2002, when the first edition was published, the only sensible path for the majority of DIY investors led straight to the Vanguard Group.

Twenty years later, the retail investment landscape has become nearly unrecognizable, and mostly for the better. Although there are still plenty of traditional stockbrokers whose streams of trading commissions cream significant wealth off the top of client accounts, increased client awareness of the importance of costs has forced many stockbrokers to stop taking commissions and instead charge management fees, which in general nick clients less.

Exchange-traded funds (ETFs) have revolutionized the mutual fund industry, mostly in a good way. The traditional open-end index fund is not obsolete—far from it. Rather, ETFs have given the retail customer the freedom to hold assets at a wide variety of brokerage firms. If you want to, there’s no reason why you can’t own a Vanguard ETF (or anyone else’s) at Schwab or Fidelity. If you’re extremely careful, you can even do so at one of the evil old brokerage firms. (In many cases, it’s possible to own Vanguard open-end funds at other brokerages, but usually by paying commissions.) Vanguard’s ETF and open-end products still provide nonpareil exposure to both the stock and bond markets, but the firm’s increasingly erratic service has forced many to hold their funds at another custodian.

If the news on the brokerage and mutual fund fronts is good, the financial media has only gotten worse. In the same way that social media has corroded both political discourse and democratic norms, it has exposed the investing public to a financial information minefield, with the 2021 GameStop frenzy as Exhibit 1. If you studiously avoid financial cable programs, the newspaper business sections, and investment-related Twitter or Facebook content, your pocketbook is sure to benefit.

CHAPTER 13

YOUR BROKER (SORRY, “INVESTMENT ADVISOR”) IS NOT YOUR BUDDY

Pretend you’re a businessperson and management has assigned you to a small country in Eastern Europe called Churnovia. (It’s located well north of Chapter 3’s Randomovia.)

Although you find the climate, culture, and cuisine to your liking, you wonder about Churnovia’s legal system, which emerged just a generation ago from the chaos of the Soviet Empire’s breakup. Mention of “property rights” and “contractual obligation” most often elicits blank stares from your local business contacts.

One day, you feel a pain in your stomach; by the time you are rushed to the hospital, you are in agony. You are whisked into surgery where your appendix is removed. You recover rapidly and are quickly discharged home. But your spouse notices something curious: while asleep, your abdomen seems to be ticking. Sure enough, you go into a quiet room and detect a faint, regular noise emanating from your midsection.

You report this to your surgeon, who nonchalantly replies, “Oh yes, it’s not unusual for bellies to tick after a bout of appendicitis.”

You are not impressed, and your concern increases as your pain persists, now accompanied by a high fever.

Your faith in Churnovian medicine shaken, you fly home, where doctors remove a wristwatch surrounded by a sack of infected tissue. This time, your recovery is not as rapid, and you are confined to the hospital for weeks of antibiotic therapy. It’s months before you can return to work.

You wonder about legal recourse and consult an expert in international law, but he’s not sanguine. “You see, there’s a big difference between Churnovian and American medicine. For starters, doctors there have no firm educational requirements. You don’t even have to go to medical school, and some haven’t even completed high school. All you have to do is cram for a multiple-choice exam, which you can take as many times as you need in order to pass, and as soon as you do, you can hang out a shingle.”

Even worse, Churnovian doctors owe no professional duty to their patients. They frequently perform unnecessary surgeries for financial gain, and when things go wrong, they aren’t held to a particularly high standard. The pièce de résistance: upon entering the hospital you signed an agreement to submit all disputes to an arbitration board whose members are chosen by the Churnovian Medical Association. Your international attorney is sorry: “I’d be a fool to take your case.”

The message of this chapter couldn’t be more clear: welcome, dear reader, to Churnovia.

A decade ago, Harvard University’s Sendhil Mullainathan sent a battalion of actors to brokers’ offices posing as prospective clients, each with a list of their current investments. A quarter of them came with simple, low-cost indexed portfolios. All but 2.4% of the brokers recommended selling the index funds and switching into a portfolio of high-cost, actively managed mutual funds, many of which sported front-end loads: fees paid directly to them and their firms. (The other three-quarters of the study’s fictitious portfolios held, variously, certificates of deposit, actively managed funds, and employer company stock.) The study’s authors concluded that “evidence suggests that adviser self-interest plays an important role in generating advice that is not in the best interest of the clients.”¹

The results of this experiment are easy enough to understand. Consider:

Images   The licensing of brokers (or registered reps, as they’re known in the business) involves no educational requirements—no mandatory courses in finance, economics, or law. Simply pass the multiple-choice Series 7 exam, and you’re good to go. In many US states, it’s harder to get licensed as a manicurist than as a stockbroker. Having read this far, you know far more about financial theory and history than most brokers do.

Images   Brokers owe no fiduciary duty to their clients. Although the legal definition of “fiduciary” is complex, it basically means the obligation to always put the client’s interests first. Doctors, lawyers, bankers, and accountants must act as fiduciaries. Not stockbrokers. For decades, the brokerage industry hewed to a weak “suitability” standard for brokers’ sales practices. Over the past decade, investment firms have relabeled their brokers “investment advisors” and conned the SEC into promulgating Reg BI (“best interest”), a mealy-mouthed regulatory structure that falls far short of a fiduciary standard by allowing firms to define for themselves what practices are and are not acceptable.*

Images   In few other professions are the service provider’s interests so different from the client’s. In a brokerage relationship, the client rationally seeks to minimize turnover, fees, and commissions, whereas it’s in the broker’s best interest to maximize these expenses. Financial humorist Fred Schwed exaggerated only slightly when he described the typical brokerage firm modus operandi as follows: “At the close of the day’s business, they take all the money and throw it up in the air. Everything that sticks to the ceiling belongs to the clients.”²

Images   Almost all brokerage houses have you agree, at the time you open your account, to resolve any future legal disputes via arbitration before the New York Stock Exchange, Inc., or the Financial Industry Regulatory Authority (FINRA), the brokers’ own trade groups.

THE BETRAYAL OF CHARLIE MERRILL

As awful as brokerage practices are today, I admit that they’ve been getting better of late.

Over the past century, the US brokerage industry has undergone a long and tortuous evolution. The best place to start is with Charles Edward Merrill. To label him as “complex” would be an understatement: self-aggrandizing and overly fond of carousing, strong drink, and other men’s wives, he was also a visionary who nearly single-handedly pioneered the financial services industry in the period surrounding World War II. The rise and fall of his dream—the brokerage company as public fiduciary—is a story worth telling.

Born in 1885, Merrill entered the brokerage business after dropping out of Amherst and quickly built a successful investment banking and retail brokerage firm. Merrill was repulsed by the corrupt financial climate of the late 1920s, with its overt stock manipulation and “bucket shops” where customers gambled on the prices of stocks without actually buying or selling them. Wall Street then was the ultimate insider’s poker game in which the investing public invariably played the sucker.

Merrill strove to be different. The 1929 crash produced a wave of popular revulsion against the brokerage industry and resulted in the passage of the legislation described in Chapter 10: the Securities Acts of 1933 and 1934, the Investment Company Act of 1940, and the now defunct Glass-Steagall Act. But for decades before this, Charlie Merrill knew something was wrong, and he wanted to fix it. In 1939, he got his opportunity and accepted the leadership of a new firm: the merged Merrill, Lynch & Co. and E.A. Pierce and Cassatt, later renamed Merrill Lynch.

Merrill undertook the job with relish and made it his mission to restore public confidence in the brokerage industry. This was a tough row to hoe, and his methods were nothing short of revolutionary. He paid his brokers by salary, not commission. Since the first “stock jobbers” began plying their trade in the coffeehouses of London’s Change Alley in the late seventeenth century, brokers had made their living by “churning” their clients: encouraging them to trade excessively and generate fat fees.

Merrill wanted to send a message to the investing public that his brokers were different from the commission-hungry rogues of his competitors. By contrast, his salaried employees would act as the objective, disinterested stewards of the public’s capital. He would not charge for collecting dividends, as did other wire houses (as brokerage firms were called because they communicated over private phone lines). Commissions would be the minimum the stock exchange allowed. Although high by today’s standards, Merrill customers would get rates offered only to the biggest clients at other firms. A Merrill broker would always disclose the company’s interest in a particular stock, something that was not required by law and unheard of elsewhere in the industry (and rarely done even today). Analytic research replaced “hot tips.”

Merrill’s revolution succeeded. When he died in 1956, Merrill Lynch had grown into the nation’s largest wire house, with 122 offices, 5,800 employees, and 440,000 customers. Yet Merrill died an unhappy man.

Although Merrill Lynch had transitioned to Main Street, the rest of Wall Street had not yet made it there. It gave the old man no satisfaction to be the leader of a failed, backward industry. Sadly, the rest of Wall Street continued to treat the client as it always had, not as an object of respect and worthy of the most effective and efficient investment product, but instead as a revenue source.

Worse was to come. Donald Regan (later US secretary of the Treasury) took over the reins at Merrill in 1968. The markets were buoyant that year. Tech stocks were all the rage and trading volume ran high. Brokers at other firms worked on a traditional commission basis and were all but printing money, a bounty not enjoyed by Merrill’s salaried brokers. Defections mounted, and within a short time after assuming the chairmanship in 1971, Regan was forced to readopt the seedy old industry practices and cut his troops in on a piece of the commission action.

Thus was the firm’s legacy, along with its clients, betrayed. In the short run, Regan saved the company; the defections stopped and profitability returned. Trading volume at Merrill skyrocketed as it reacquired the ethics of the rest of the industry. Instead of treating its clients’ interests as a sacred trust, the company turned them back into cash cows to be milked methodically for commissions.³

This marked the end of the trail for the modern, full-service retail brokerage firm as a socially useful enterprise. It fell to others to champion inexpensive access to the markets for the average investor, most notably Jack Bogle at Vanguard.

***

When I wrote this book’s first edition in 2002, the ocean of investment industry sleaze had once again reached the flood-tide stage. Most clients, for example, did not understand the enormous toll their brokers extracted from the spread between the “bid” and “ask” price of traded securities. In many cases, brokers charged up to several percent per transaction; this was emphatically true when they traded municipal and corporate bonds.

In this instance, the broker was acting as an “agent,” trading with another investor, usually at another brokerage. A brokerage cannot benefit from the spread, but is only allowed to collect a commission on the service.

In many cases, however, the brokerage sold from its own inventory, in which case the profit margin was much higher than with an agent/commission transaction. With these so-called principal transactions, the client almost never found out that the purchased stock or bond came from another of the firm’s customers at a much lower price. Clients were often told simply that “there is no commission” on principal transactions, as if they had just benefited from an unexpected bit of corporate largess, when in fact they were paying a substantial spread. (Although illegal, charging a commission on a principal transaction—“double dipping”—was not rare.)

Even worse, many wire houses’ principal transactions were “specials”: undesirable stocks and bonds the firm underwrote or purchased in quantity and sold to clients by brokers with glowing research reports from the company’s crack analysts. Brokers who unloaded large amounts of such toxic waste on their unsuspecting clients were rewarded with bonuses and prizes (typically exotic vacations).⁴ Until relatively recently, brokerage statements were commonly laced with obscure, illiquid stocks and bonds that carried high commissions and spreads, positions that had “special” written all over them.

Stockbrokers still offer stock recommendations, which are another source of monkey business. The average broker is a salesperson, not an expert in finance. Generally, his stock picks come straight from the current-day version of the “squawk box,” a loudspeaker that connected every branch to headquarters. Several times a day, the firm’s industry analysts report their conclusions simultaneously to thousands of brokers around the country. Later on, clients get the hot tip from their broker.

The retail client is last in line. The large institutional players—pensions, privately managed money, and mutual funds—get the news long before the typical client. Stock prices are already bid up by the time a broker phones a client with the recommendation. In this card game, the client is the patsy.

The analysts’ recommendations were, and still are, tainted. Analysts feel immense pressure to recommend the stocks of companies that their firms underwrite (i.e., the selling of freshly minted shares) or would like to underwrite. Analysts are frequently threatened with firing for making unfavorable recommendations about these companies, so they virtually never suggest selling their stocks. “Hold” is the worst recommendation they give. In 2017, for example, only 6% of analyst ratings were “sell.” During the dot-com mania of the late 1990s, sell recommendations fell to just 1% of the total.⁵

THINGS SLOWLY IMPROVE

Until recently, the broker who creamed less than 2% off the top of his client accounts was probably asking his parents if his childhood bedroom was still available. In the past few decades, investors are getting a fairer shake, even at wire houses. Investors are more aware of the importance of fees and commissions to investment returns. The wire houses have responded by moving away from commissions and toward a fee-based structure in which they charge around 1%–2% of assets under management. Brokerage firms have refashioned their “brokers” as “investment advisors,” who still do not meet anything close to the fiduciary standard mandated by the 1940 Investment Company Act.

Clients of the current crop of broker/investment advisors, newly educated about the benefits of low-cost index funds, expect that their portfolios will reflect this knowledge. Today’s investor can put together a perfectly serviceable portfolio with just one or two domestic funds and one or two foreign funds, and many are now unhappy about being charged 1% or more for such simple portfolios.

So the new breed of investment professional sells what it can: complexity. A typical brokerage customer’s account these days likely consists of a rotating cast of scores of individual stocks, mutual funds, and ETFs with grossly overlapping holdings. While a 1%–2% fee on such a portfolio is still an effective way to transfer assets from you to your brokerage firm, it admittedly is an improvement over the old commission-based model. If you’re especially unlucky, you might still retain one of the bad old commission-based stockbrokers who will happily recommend portfolios consisting exclusively of individual stock and bond securities that are carefully curated by their “research” departments for your consideration, as well as non-publicly traded real estate securities, private equity, venture capital, or hedge fund vehicles.

HOW CAN I TELL THE GOOD FROM THE BAD APPLES?

Twenty years ago, the investment business landscape was stone simple from the individual’s perspective. Stay away from any stockbroker or brokerage house. Instead, purchase index mutual funds directly from a low-cost provider, with the Vanguard Group as the default choice.

As already noted, things are better today. For those who need an advisor, fees have fallen dramatically. If you’re willing to execute your own trades, paying for advice on an hourly basis is an efficient way to go. The new robo-advisors, which will execute an indexed strategy for 0.15%–0.50% of assets under management, are halfway between a hands-on money manager and doing it yourself. As a general rule, those who need an advisor should:

Images   Avoid any advisor who deploys actively managed mutual funds, particularly more than one of them in a given asset class.

Images   Avoid any advisor who recommends “alternative” asset classes, such as hedge funds, private equity, private real estate, or venture capital vehicles.

Images   Pay attention to fees. Depending on the size of your portfolio, turn your nose up at any fee even approaching 1% of assets. If you’re comfortable executing trades on your own and need only intermittent advice, pay for it by the hour.

Images   Ensure that your advisor acts as a fiduciary. The easiest way to accomplish this is to have the advisor sign a fiduciary oath (currently available at http://www.thefiduciarystandard.org/wp-content/uploads/2015/02/fiduciaryoath_individual.pdf). If your advisor hesitates, don’t walk, run.

If you’re wealthy, avoid becoming a “whale”: the high-net-worth cash cows of the investment industry. Most of the “exclusive” investment vehicles available to whales—separate accounts, hedge funds, limited partnerships, and the like—are designed to bleed them with commissions, transactional costs, and other fees. Advisors court their large cetaceans with impressive descriptions of sophisticated research, trading, and tax strategies, to say nothing of fancy dinners and sports tickets. As already discussed, the largest, savviest institutional players don’t, on average, beat the market; what exactly makes you think that you can?

Swallow your pride and stick to low-cost index funds and trade bragging rights at the country club for the quiet satisfaction of investment returns higher than those of your high-rent-district neighbors.

THE INSURANCE COMPANY SWAMP

Buy insurance to insure yourself, not to invest. A family’s sole breadwinner should purchase term life insurance only if he or she lacks sufficient assets to provide for a spouse and dependent children in the event of the breadwinner’s untimely death. The same goes for disability insurance, although this is becoming increasingly expensive. Since most disability policies come with long waiting periods, increasing premiums with age, and cease at age 65, they make progressively less sense the older one gets.

Probably the most fraught insurance area is long-term care, which over the past decade has seen dramatically increasing premiums and decreasing benefits. In the best of all worlds, the retiree accumulates enough assets to self-insure.

Do not purchase insurance products for investment. While these have the benefit of tax deferral, they come with high fees, hefty surrender charges, and the risk of payout reduction. These products are largely regulated by state laws, which generally tolerate a greater level of unscrupulous practices than the federal regulation of brokerage firms does.

Avoid variable universal life insurance policies, a mind-bogglingly complex product at extremely high expense and penalty risk.

Avoid whole or universal life insurance, which generally costs far more than term insurance. Because of the complex fees and potential withdrawal penalties, you’re nearly always far better off investing the premium difference in a prudent low-cost portfolio of stock and bond index funds, especially in an IRA, which also carries a tax-deferral benefit.

And avoid at all costs fixed indexed annuities. Don’t be fooled by the name. These are stock index funds in the same way that Don Corleone was Catholic. Yes, their returns are linked to a stock index, typically the S&P 500, but because their annual returns are capped, their long-term returns are consequently much lower. In exchange for never losing money, this vehicle caps returns during the best years, which produces the lion’s share of capital appreciation, and siphons off the stock dividends that account for the rest. These policies also have early termination and exchange penalties.

If you’re unlucky enough to have a fixed index annuity pitched to you, you should present the six questions formulated by my colleague Allan Roth:

1.   At what return is the fixed index annuity capped? Some caps are as low as 4.5%.

2.   Can the insurance company lower the cap in the future?

3.   Does the return exclude the stock index’s dividend payout?

4.   If I cash out, are all the taxes on the sale payable at once?

5.   Isn’t some of my payout just return of principal?

6.   What are the withdrawal penalties?*

The preceding list doesn’t even begin to exhaust the products offered to gullible clients. Don’t purchase life insurance to fund estate taxes, a strategy that rarely pays off after the insurance company and agent take their cuts. Insurance salespeople are masters of psychological manipulation and pitch these products with narratives precisely engineered to stimulate our reptilian brains: Do you want to leave your family destitute? Don’t you want to avoid taxes? Wouldn’t you rather have life insurance that’s permanent and doesn’t expire? Why shouldn’t you get stock returns without the downside risk?

CHAPTER 13 SUMMARY

The financial industry has become a less dangerous place, but you’ll still need to exert caution.

Images   Many national brokerage firms, such as Fidelity and Schwab, offer low-cost investment options with good customer service. At both places you can purchase inexpensive in-house index funds, other firms’ ETFs, and Treasuries at auction at no fee. These options are the brokerage house version of the 19-cent bananas at Trader Joe’s. They’re loss leaders, designed to get you in the front door. They hope you’ll purchase more profitable services, particularly ones that involve a representative for advice; stock, bond, and options trading; and/or high-cost active mutual funds. Under no circumstances should you deal with an “independent brokerage” firm that does not offer a low-cost service.

Images   Purchase insurance products only to insure, not to invest, and stop paying for them when you have enough assets to provide for your spouse and dependent children.

Images   If you can handle your own accounts and transactions but feel the need for advice, pay for it by the hour. If you need advice and ongoing, hands-on management, use either a robo-advisor or a live advisor whose total costs, including mutual fund fees, run less than 0.50% per year. Ask your advisor to sign a fiduciary pledge. Under no circumstances pay your advisor sales commissions.

* See, for example, a letter written to the SEC chairman Gary Gensler by Barbara Roper, a highly respected consumer advocate, https://consumerfed.org/wp-content/uploads/2021/04/Letter-to-Chairman-Gensler-on-Advice-Standards.pdf, which called Reg BI “too weak and undefined to deliver the promised protections of a true best interest standard backed by meaningful restrictions on harmful incentives.” Gensler was impressed enough by this letter to hire Roper as a senior advisor.

* From Allan Roth, “6 Questions to Ask Before Buying a Fixed Indexed Annuity,” https://www.cbsnews.com/news/six-questions-to-ask-before-buying-a-fixed-indexed-annuity/.

CHAPTER 14

THE IMPROVING MUTUAL FUND SCENE

We’ve just seen how the brokerage industry isn’t quite the minefield it used to be. The finance industry’s second major leg, mutual funds, has become even friendlier to the small investor. While dangers aplenty remain strewn about this playground, they are now easier to avoid.

***

The mutual fund—pooled diversified portfolios of stocks and bonds—first appeared in late eighteenth-century Holland, and over the last half of the twentieth century became a major part of the financial markets. During the run-up to the 1929 crash, Goldman Sachs created a number of disastrously leveraged investment trusts that almost immediately blew up. These were essentially the equivalent of today’s “closed-end” funds. The Goldman trusts’ demise spurred the Investment Company Act of 1940, which led to the rapid spread of the relatively trouble-free, modern “open-end” fund. The company can create or retire shares at will when investors want to buy or sell them. Relatively few fund scandals and malfunctions have occurred since the act’s passage.

Before the 1950s, mutual funds were a small and staid part of the investment landscape, conservative operations with ongoing annual expenses around 0.5%. Unfortunately, almost all of them also featured a 7% to 9% front-end sales load on the initial sales price, which obliterated their low ongoing expense. Only a few percent of their $5 billion under management was held in vehicles sold without that sales fee—no-load funds. The first of these were the Scudder, Stevens & Clark Balanced and Common Stock funds, established, respectively, in 1928 and 1929.¹

The first mutual fund trap to avoid is thus any fund with a sales load. The sales fees are usually front-loaded (“Class A shares,” paid on purchase), but can also be back-loaded (“Class B shares,” paid on sale), or ongoing (“Class C shares”). Buy a “load” fund and you get nothing from the sales fee, which goes to the broker/salesman/brokerage house. Less than nothing, in fact; load funds on average underperform no-load funds by a slight amount, even after their load fee is paid.²

GUNNING THE FUND

For a few decades following Gerald Tsai’s Manhattan Fund debacle in the 1960s, the mutual fund world went to hell, a slide accentuated in the 1980s when Fidelity invented “gunning the fund.” Perhaps the most unfortunate example of this phenomenon was its Select Technology Fund, which in mid-1983 sported a blistering 162% 12-month trailing return.

Until that point, Fido’s reclusive chief, Edward Crosby “Ned” Johnson III, had been reluctant to publicize his funds. But persuaded by one of his lieutenants, he instructed the fund’s young manager, Michael Kassen, to cooperate with a cover story in Money, to the point of posing outdoors in the middle of a Boston February in shorts, grasping a squash racket.

The article’s headline was “How to Invest in Mutual Funds. They’re the Safest Surest Way to Invest in a Surging Market.” Within several weeks, new investors poured so much money into the fund that it tripled in size to $650 million, an enormous inflow in those days.

Kassen himself was less than ecstatic. The fire hose of inflows ballooned the impact costs of trading the small firms he favored. Not long thereafter, the tech market collapsed and presented his new shareholders with a steep tuition bill from the “college of the capital markets.”³

This sequence highlights what we might call the mutual fund hierarchy of happiness. At the top is the fund family. Fidelity collected more than 1% in ongoing fees and 3% in front-end loads on Select Technology’s $650 million in assets, no matter how it performed. The fund manager is less happy. He faces the formidable job of investing a mountain of cash in a small corner of the market, an inconvenience cushioned by his superstar status–driven salary increase.

Investors are at the bottom. About the only thing they get is the faint glow of association with the fund manager’s soon-to-disappear fame. In this situation a fund company might not be able to resist piggybacking higher management fees on its new popularity, the likelihood that its investors have just piled into a sector or style that has topped out, and the certainty that the fund’s torrent of inflows will be invested with a maximum of market impact.

After garnering nearly $1 billion in assets in 1983 and 1984, the tech market turned stone cold, underperforming the S&P 500 by an average of 20% in each of the next six years. By 1989, fund assets had fallen to just $71 million. At that point, the fund’s performance turned around, and it gradually began to accumulate assets again, finally reaching the $1 billion mark during the late-1990s tech bubble. In 1998, it beat the S&P 500 by 66%, and in 1999, as the dot-com mania heated up, by 96%. Within 12 months, assets quintupled to $5.2 billion, just in time for the tech collapse of 2000.

The story of Select Technology illustrates the perverse nature of fund flows, which serve as contrary indicators. Funds in high-performing market sectors tend to attract piles of assets. In industry parlance, this is known as hot money: assets thrown by naïve investors at high past performance. That performance is usually the result of the conjunction of two lucky draws: industry sector performance and manager stock selection.

Hot money accumulation more often than not heralds a peak price in its market sector. Even if it doesn’t, excessive inflows of hot money certainly serve as a drag on fund performance, as funds are forced to deploy a large amount of capital in a fixed number of existing company shares. Over the past four decades, Fidelity Select Technology hasn’t done too badly, performing in line with other technology funds in a sector that has slightly outperformed the broad stock market. But that creditable performance is only in “time-weighted” terms—the return of the fund itself. Share owners in red-hot funds buy high and sell low, stuffing them with cash at market tops and withdrawing money during tech collapses, thus earning a much lower “internal rate of return” than the fund itself.

This is a more general phenomenon in the fund industry, where poor timing decisions earn the typical mutual fund investor about 1%–1.5% less than the underlying fund return. A good general rule is that the hotter the asset class, the larger that gap. A study by Russell Kinnel at Morningstar found a gap of 0.4% for sleepy large-cap value stock funds and a 3.4% gap for more glamorous large-cap growth stock funds. The largest gap, 13.4%, was for technology stock funds like Kassen’s.⁴

In the digital era, social media flogs mutual funds even more effectively than old-style investment company advertising. After all, who needs to buy ads when you have a million Twitter followers?

Fund flows highlight the conflict of interest between investors and the fund companies. Just as the brokerage firms exist to make clients trade as much as possible and insurance companies sell products that, because of their expense and complexity, can’t help but underperform, the fund companies exist for one purpose: to collect assets, no matter what they return.

Finally, I can’t help but mention the Morningstar “Buy the Unloved” strategy. Since Morningstar is located in Chicago and staffed by Cubs fans, they have a special affinity for losers. Each year they sort the inflows and outflows of fund categories and measure the average performance of the three most popular and unpopular fund categories for three years. Between 1994 and 2021, the “unloved” fund categories returned 11.9%, versus 6.7% for the “loved” categories. The unloved fund categories also handily outperformed both domestic and international broad market indices.⁵

I don’t recommend this strategy, since it can be badly under-diversified. Still, the loved categories are excellent examples of the dangers of chasing performance and of asset classes’ inherent tendency to “mean-revert,” following bad performance with good and vice versa.

WHEN MUTUAL FUNDS GO BAD: VARIABLE ANNUITIES

Variable annuities, which mix insurance and investment, are a close relative to the load mutual fund. Like load funds, most come with high sales fees and ongoing insurance charges that are often higher than those of load funds.

These products are not bought—they are sold. Although they compound free of taxes until they are redeemed, this advantage is only rarely worth their egregious fees. Adding insult to injury, a large chunk of these are sold by insurance agents, financial planners, and brokers for retirement accounts, where the tax deferral is unnecessary. Consider an advertisement from a few decades ago for one such product in Financial Planning magazine, a trade publication for investment advisors:

Now an annuity that keeps paying,

and paying      

and paying      

and paying      

and paying      

and paying . . .

The advertisement went on to explain how the product paid the salesperson a 4% upfront commission plus a 1% “trail” fee each year. The ad urged the magazine’s investment-professional readers to “find out more about the annuity that keeps paying and paying and paying. . . .”⁶ Guess who did the paying and paying and paying every year?

There is perhaps one circumstance in which you should consider a variable annuity: an investor under age 40 with no tax-sheltered assets who wants exposure to a tax-inefficient asset class such as REITs or high-yield bonds, and can get that from a low-cost product, such as that offered by Vanguard through Transamerica. If you’re stuck with a high-cost variable annuity from one of the industry’s bad actors, consider a 1035 exchange to an account with a low-cost provider such as Vanguard/Transamerica, Fidelity, or Dimensional.

In general, steer clear of mutual funds and variable annuities with sales loads and fees. Buy only true no-load funds and annuities that do not carry fees of any type, including 12b-1 fees. Better yet, stay as far away from insurance salespeople as you can.

***

In the two decades since this book’s previous edition, the mutual fund landscape has become far more investor friendly. This has happened for two reasons.

The first reason revolves around the remarkable story of John C. Bogle, whom we briefly encountered in Chapter 3 as the interested reader of Paul Samuelson’s 1974 essay, “Challenge to Judgment.” At that moment, Bogle was fighting for his professional life. In the early 1960s, the recent Princeton graduate had plunged headfirst into “go-go” style money management in his first job at the renowned Wellington Management firm.

Unaware of the pioneering work by Fama, Sharpe, and others, the young Bogle bought shares in the darlings of the era—Xerox, IBM, Avon, and Polaroid, and others, collectively labeled the “Nifty Fifty.” This misplaced enthusiasm led him to partner with a hotshot Boston tech analyst firm, Thorndike, Doran, Paine & Lewis, to transform the Wellington Fund, Wellington’s previously conservative flagship product, into a high-performance vehicle. Several years later, the collapse of the Nifty Fifty hit Wellington Fund hard and its Boston partners canned Bogle.

Wellington Management had picked the wrong man to fire. At this point, most money managers would have pulled in their horns, spent time with family, and slowly ventured back into the investment business. By happy coincidence, Bogle had written his 1951 Princeton senior thesis on the mutual fund business. Few fund managers knew the ins and outs of its playbook—the Investment Company Act of 1940—as well as he did. Among other things, the act mandated that fund directorship be separate from that of the companies that provided their advisory services, in this case Wellington Management. Fortuitously, only a few of the fund’s directors worked for the management company. After months of acrimonious debate, the Wellington Fund declared its independence from Wellington Management, and on September 24, 1974, Vanguard was born with Bogle at the helm.

At a stroke, Bogle became his own man, free to let loose upon an initially unappreciative public his own private vision of a great investment company utopia: The World According to Bogle.

The new company demonstrated his revolutionary genius by establishing an ownership structure never before seen in the fund industry. It involved creating a “service corporation” that ran the funds’ accounting and shareholder transactions and was owned by the funds themselves. Because the service company, Vanguard, was owned exclusively by the funds, and the funds were owned exclusively by its shareholders, the funds’ shareholders were in reality Vanguard’s owners. Vanguard became the first and only truly “mutual” fund company: one owned by its shareholders. Vanguard therefore had no incentive to milk its customers, because they were also Vanguard’s owners. Its only imperative was to keep costs down.

Recall Samuelson’s dictum about mutual funds: “As there is only one place for a temperate man to be in a saloon, behind the bar and not in front of the bar.”⁷ In other words, the biggest profits in mutual funds are not made from investing in them, but rather from managing and selling them. To save his career, Bogle convinced his fellow fund board members to forego those profits by “mutualizing” Wellington. Moreover, apropos Samuelson’s metaphor, Bogle moved his mutual fund shareholders from in front of the bar to behind it.

The mutualized structure, where customers own the company that serves them, is not in itself a new concept. It was not uncommon in the life insurance business. But at the time it was unheard of in the mutual fund business. (In recent decades, Vanguard has set up fund operations abroad, where their shareholders do not benefit from the mutual ownership structure.)

Bogle was a complex, driven character who was not above bending historical narrative to his purpose. In 1960, when he was still a young hotshot analyst at Wellington, Bogle wrote an article in Financial Analysts Journal under the pseudonym “John B. Armstrong” that ridiculed the idea of passive management. He probably adapted that pen name from that of his grandfather Philander B. Armstrong, an insurance executive who excoriated corrupt industry practices in the late nineteenth century. As Jason Zweig told author and analyst Eric Balchunas,

One of my pet theories about Jack is that he cast himself as the outsider, like Shane riding in on the horse. But he was the ultimate insider. What happened is he got thrown out from the inner circle. Running Wellington Management in the late sixties is hardly an outsider job. It’s sort of like being secretary of state or Speaker of the House. He was not only an insider but he was also in the innermost circle. Then he got thrown out. And what did he do? He made a virtue out of necessity.⁸

Fortune blessed Bogle with extraordinary intellectual suppleness; by the time Vanguard began actual fund operations in 1975, Bogle had read Charles Ellis’s article “The Loser’s Game” in Financial Analysts Journal, which noted that 85% of pension accounts underperformed the stock market. Bogle cracked open the annual edition of Weisenerger Investment Companies and calculated by hand the average pension fund return over the past 30 years. The funds listed underperformed the S&P 500 by an average of 1.4% per year. Just matching the market would be an improvement, an insight that led Bogle in 1976 to offer an index mutual fund, initially named the First Index Investment Trust (FIIT), which tracked the S&P 500.

In the event, FIIT was anything but “first”: Several years before Bogle’s Damascene conversion, multiple academically oriented types, steeped in Fama’s efficient market hypothesis, had started small passively managed funds at Wells Fargo, American National Bank, and Batterymarch. Aimed mainly at pension funds, these efforts collected only minuscule assets. These banks, particularly the sizable Wells Fargo, might well have beaten Vanguard to the retail index fund punch had that not been forbidden by the Glass-Steagall Act.

FIIT nearly flopped, its initial underwriting garnering a scant $11 million. The doubters were gleeful, labeling the FIIT “Bogle’s Folly.” Fidelity’s Ned Johnson delivered the unkindest cut of all in the Boston Globe: “I can’t believe that the great mass of investors are going to be satisfied with just receiving average return. The name of the game is to be the best.”⁹

Vanguard’s mutualized structure was, and remains, unique in the mutual fund industry. With 20/20 hindsight, FIIT’s success seems almost preordained by the dynamics of Sharpe’s “arithmetic of active management”: While over short periods of time, the approximately 1% per year expense advantage over its actively managed peers is hard to detect, over longer periods, the Randomovian noise of relative manager performance washes out, leaving only the indexing expense advantage. As journalist and author Jonathan Clements says, “Performance comes and goes, but expenses are forever.”¹⁰

In a sort of slow-motion avalanche, the simple combination of arithmetic and statistics fed on itself in an unstoppable virtuous cycle. The renamed 500 Index Fund gathered more assets, which drove an economy of scale that lowered the expense ratio from its 1976 starting level of 0.66%. The fund’s decreasing expense lengthened its performance lead over its actively managed competitors and attracted yet more assets, which further decreased its expense ratio, further increasing its performance edge. At year-end 2022, the fund’s expense ratio is 0.04%, and its ETF share class runs at a 0.03% expense.

Buoyed by the success of the 500 Index Fund, Vanguard began to launch other passive vehicles, starting with the Total Bond Index Fund in 1986 and the Total Stock Market Index Fund in 1992. The latter targets all the stocks trading in US markets, not just the evolving names in the S&P 500.

As ever more index funds attracted ever more assets, their advantage over actively managed funds increased and spawned funds that track a dizzying variety of indices. In 1988, Fidelity’s Ned Johnson provided Bogle with one of the most delicious moments of his career when Fidelity, stung by the loss of assets to Vanguard, introduced its own index funds. In 2018, Fidelity introduced a family of zero expense index funds in the desperate hope that their buyers would be tempted by higher-margin items.

Figure 14.1 tells the tale of index fund assets’ explosive growth.

FIGURE 14.1 Assets of actively managed and indexed stock funds

Source data: Michael Nolan, The Vanguard Group

At year-end 2022, stock index fund assets are about equal to actively managed fund assets. (Active fund assets have also increased, but only because of their investment return. In every single year since 2006, net assets have flowed out of actively managed funds and into index funds.) By mid-2022 the world’s two biggest asset managers, by a wide margin, were BlackRock, whose primary products are passive, and Vanguard. They are followed by UBS and Fidelity, each of which manage half as much in assets, followed closely by State Street, which is also mainly an index shop.¹¹

Bogle, who passed away in 2019, did not die poor. Still, his revolutionary restructuring of Wellington/Vanguard transferred potential billions from his pockets to those of his customers, and then from the pockets of the other mutual fund companies forced to compete with Vanguard’s low fees.

ACTIVE FUND FAIRY TALES

As you might imagine, the mutual fund industry didn’t appreciate index funds eating its lunch. It’s devised any number of reasons why you shouldn’t invest in index funds, from Ned Johnson’s assertion that investors shouldn’t settle for average performance to Sanford C. Bernstein & Co.’s fatuous “The Silent Road to Serfdom: Why Passive Investment Is Worse than Marxism.”¹² (I’m not connected to this investment firm.)

The myth that refuses to die, however, is that actively managed funds protect their investors in bear markets. This is flatly untrue. Standard and Poor’s produces an annual mutual fund performance scorecard. The 2008 edition analyzed the relative performance of index and actively managed funds during the 2000–2002 and 2008 bear markets. In both cases, in 11 of their 12 fund categories, the majority of actively managed funds underperformed their benchmarks.¹³

When instructors present the efficient market hypothesis to their students, one usually asks, “But, Professor, if everyone indexes, won’t prices get out of whack, which will misallocate capital and hurt the economy?”

This question seems reasonable until you realize that what matters is not what percentage of assets is indexed, but rather what percentage of trading is indexed. Since actively managed funds trade about 10 times as frequently as indexed ones, if just 10% of funds are run by active managers, they will still do roughly half of the trading. That’s more than enough to support efficient price discovery.¹⁴

Another canard about indexing’s rise is that at some point the markets will get enough out of whack to let active managers thrive. This is mathematically impossible. If passive investors own 99% of the stock market, the remaining 1% of the market will still be identical to the overall market. The average active manager will continue to get the market return on the unindexed 1% of stocks minus their expenses.¹⁵

A more serious issue surrounding indexing’s triumph is the political and economic danger posed by the three biggest indexers—BlackRock, Vanguard, and State Street—which own about half of the US stock market. Just before he died, Bogle recognized that, given the self-reinforcing economy of scale I’ve described, it is almost impossible for new entrants to challenge this Big Three.

Moreover, this concentration of stock ownership has the potential to worsen the nation’s wealth and income inequality and to concentrate the increasing “winner take all” phenomenon seen in the telecom, airline, and tech arenas. This question lies well beyond the scope of this book. Interested readers should consult Harvard Law School’s John C. Coates’s “The Future of Corporate Governance Part I: The Problem of Twelve.”¹⁶

INDEX FUNDS IN DRAG

Exchange-traded funds (ETFs) now dominate the fund world. These mutual funds are similar in many respects to the old closed-end funds (CEFs), which have been around for more than a century and consist of portfolios of stocks and bonds that trade throughout the day on the stock exchange, but with three important differences. First, the overwhelming majority of ETFs are passive or index funds; CEFs are actively managed. Second, CEFs can trade at a substantial discount or premium to the net asset value (NAV) of the securities they hold, but an ETF’s market price is kept very close to its NAV by arbitrageurs known as “authorized participants” (APs), who also create and liquidate ETF shares. APs stand ready to buy the ETF and sell the underlying securities when the ETF trades at a discount to NAV, and to do the opposite when the ETF trades at a premium to NAV. Third, CEFs comprise a tiny piece of the investment universe. ETFs, whose assets have surpassed those of traditional open-ended funds—both passive and active—are taking it over.

To his dying day, Bogle didn’t think much of ETFs, which he saw as speculative vehicles, “like handing a match to an arsonist.” He did his best to prevent Vanguard from offering them before the company’s bylaws forced him off its board in 1999, on his seventieth birthday. Bogle’s departure allowed Gus Sauter, Vanguard’s index fund engineer, to begin the company’s launch into that area.

It’s a good thing Bogle didn’t get his way. Equity ETF assets have surpassed those of traditional open-end stock index funds for multiple reasons:

Images   Because they are cheaper for the fund family to service, ETFs have slightly lower expense ratios than corresponding open-end funds. For example, the ETF class of Vanguard’s biggest fund, the Total Stock Market Index Fund, has a 0.03% expense ratio, versus 0.04% for the Admiral class open-end shares.

Images   Nearly all ETFs can be held and traded commission-free at most major brokerage firms, whereas trading fees are usually charged on most open-end funds not issued by the brokerage firm itself.

Images   The ETF redemption mechanism generally avoids the capital gains distributions that can plague some open-end index funds and are thus more tax efficient. This ETF tax advantage does not apply at Vanguard, however, which patented an arcane transactional method that extends this tax efficiency to their corresponding open-end funds.

Images   For those who want to tilt toward value and small stocks, a wide range of fund families offers ETFs that provide exposure. The list includes Dimensional Fund Advisors, whose open-end funds still require paying an advisor.

Images   Most important, ETFs treat long-term shareholders more fairly than do open-end funds. Open-end funds “internalize” their trading costs by exposing a fund’s long-term shareholders to the costs incurred by those who frequently trade in and out of it. ETFs, on the other hand, “externalize” the trading costs via the bid/ask spread each time a shareholder buys or sells. This externalization of trading costs is what ultimately quelled the fears of Sauter and others at Vanguard about exposing their fund assets to “hot money” flows.¹⁷

All that said, the preceding ETF advantages do not come for free. First, the bid/ask spread on the purchase and sale of an ETF can eat up many years of expense advantage. Most brokerage firms—“custodians” in finance lingo—farm out their ETF trades to market makers who profit from the spread. The market makers then kick back part of that profit to the custodians. It’s win-win for the custodian and the market makers, but lose-lose for the client. The more thinly traded the ETF, the bigger the problem. This isn’t much of an issue, for example, for Vanguard’s huge Total Stock Market ETF, VTI, which trades at a minuscule spread, but the spreads on smaller ETFs can run well in excess of 0.10%. These spreads can vary greatly throughout the day, especially during the first and last half hour or so of trading. The investor thus needs to be careful to execute all ETF trades as limit orders to avoid a suddenly widened spread. For this reason, it’s also a good idea not to trade an ETF before 10 a.m. or after 3:30 p.m. Eastern time.

Second, ETF bond funds that trade corporate and municipal securities suffer from a liquidity mismatch between the theoretically highly liquid ETFs and the often highly illiquid bonds ETFs hold. During the market turmoil of late 2008 and March 2020, ETFs that owned municipal and corporate securities, including total bond market index ETFs, traded at wide spreads. ETF sellers during these periods obtained significantly lower prices than the owners of the corresponding open-end funds, who could buy and sell the funds at the same price: the 4 p.m. closing NAV.

Third, the fact that ETFs can be traded throughout the day presents the investor with a classic “paralysis of choice” problem: deciding when to pull the trigger while watching the ticker bounce up and down. With a traditional open-end fund, that decision has already been made for you. You’re getting the 4 p.m. price, whether you like it or not. For many ETF investors, the continuous trading issue generates no small amount of stomach acid. (ETF proponents can, of course, make exactly the opposite case. They like knowing precisely what price they’re going to get, instead of settling wherever the market happens to close.)

Fourth, when a traditional open-end fund accumulates so much assets that they impair the manager’s ability to trade efficiently, she can close the fund, as Fidelity eventually did with Magellan and Vanguard did with Primecap. This is not much of a problem with total-market or large-cap index funds, but it can be an issue with passively managed index funds in small corners of the market. This happened to Dimensional Funds in the early 2000s when it closed its US Small-Cap Value Portfolio. ETFs, on the other hand, don’t have this mechanism and thus can’t protect long-term shareholders from hot-money flows.

In addition, ETFs may suffer even more than open-end funds from their issuers pandering to hot-money flows from gullible investors, and the ease with which ETFs are traded probably magnifies the dollar/time-weighted returns gap even more than for traditional open-end sector funds. Some of the most notable, now shuttered, were the HealthShares Dermatology and Wound Care ETF, and the Direxion Daily Agribusiness Bear 3x Shares (COWS). The latter was a particularly egregious example of “leveraged” funds that magnify an index’s daily moves—in COWS’s case, three times the opposite of its index. Because of their mathematical characteristics, which I’ll describe in more detail in Chapter 18, avoid inverse and leveraged funds.

For the long-term investor, there’s not much practical difference between the two structures, which function as wrappers for the assets they contain. Your sandwich tastes the same no matter the color of the bag it came in.

ARE THERE ANY GOOD ACTIVELY MANAGED FUNDS?

Indexing beats active management because of costs, not stock selection. There’s no theoretical reason that an actively managed fund can’t perform as well as a passive fund. The best place to look for a good actively managed fund is Vanguard, whose Wellington and Wellesley balanced funds (roughly 60/40 and 40/60 stock/bond, respectively) have served their investors well over the decades. A detailed study by Kenneth Reinker and Edward Tower at Duke University, for example, showed that Vanguard’s actively managed funds underperformed their passive funds by exactly the expense difference between the two.¹⁸

The other actively managed funds worth mentioning are the Dodge & Cox Fund and Vanguard Primecap. The latter has slightly outperformed the S&P 500 over the past few decades, while the former has slightly underperformed it. Both relative performances are most likely the result of the growth stock dominance in this period. I don’t recommend investing in actively managed funds, but if you can’t resist the urge, I suggest you choose funds that have low expenses, have low turnover, and have been around for decades. Dodge & Cox, for example, was founded in 1931. Vanguard’s venerable Wellington Fund, and its more conservative sister, Wellesley Income Fund, are decent balanced fund choices.

CHAPTER 14 SUMMARY

Images   Stick to index funds. If you can’t resist buying an actively managed fund, choose one with low expenses, low turnover, and a long history.

Images   Exchange-traded funds have done a superb job of increasing the availability of passive investing vehicles. Exercise caution in buying and selling these funds, and in choosing the brokerage firm that holds them.

CHAPTER 15

INVESTMENT PORNOGRAPHY AND YOU

Inspired by modest market turbulence in 2022, I just couldn’t resist trying my hand at a daily financial column. Only the names have been changed to protect the clueless.

There’s No Place to Hide in This Market

Hyman Q. Hackwriter         May 15, 2022

Nothing seems to work anymore. According to research firm Coinflip Analytics, the S&P 500 is down more than 15% for the year; the widely followed Blimber Aggregate Bond Market Index is off 14%, and what investors had heretofore considered the safest bet of all, the long Treasury bond, has seen a third of its value amputated. Tech stocks? Utilities? Cryptocurrency? Fuggedaboutit.

According to Paul Pecksniff, an equity strategist at wealth management firm Churnum, Burnum, and Howe, “Valuations are stretched, credit spreads have widened, and the market is anxious about Sweden and Finland joining NATO.” He favors companies with wide moats selling at bargain prices, such as the digital currency giant CoinSmash and BoingBoing Technologies.

“I’m scared to death of stocks right now,” says Brian Smallsaver, a twenty-something programmer and social media influencer. “And what’s the deal with bonds? Aren’t they supposed to save my bacon when stocks get creamed?”

“A lot more air’s coming out of the market’s tires,” says Fritz Mozillo, economist at Jones James, an independent brokerage firm headquartered in Boca Raton. “We’re telling clients to batten down the hatches and keep a sharp weather eye on the Fed.”

One casualty of the recent turmoil in both the stock and bond markets has been the traditional 60/40 portfolio, which an increasing number of observers consider obsolete. One of them is Frederick Fintwinch, chief portfolio manager at mutual fund giant GreenStone, who told me via email: “The conventional asset class correlation grid has gone to 1.0, and you’ve got to think outside the investables box.” He recommends prize llamas, rare Prussian postage stamps, and celebrity belly button lint.

I reached out to Dermot Landsdale III, CEO of Gigantic Global Capital, who conveyed even deeper worries from the World Economic Forum in Davos: “What we’re seeing now is a titanic battle between buyers and sellers, compounded by central bankers around the world who have deployed a dangerous mix of pushing on a string, trimming their sails, and mixing their metaphors.”

Retail investors have become increasingly distraught at the lack of shelter for their shrinking portfolios. Retired 79-year-old dentist Percival Sweedlepipe had placed most of his IRA assets into the Dolittle Technology Fund and feels betrayed by the media’s breathless coverage of its manager, Fred Wopsle: “If you can’t trust The Wall Street Journal, The New York Times, and Kiplingers, who can you trust?”

This piece, a mash-up of several articles from the business sections of national newspapers from early 2022, is recognizable as satire only because I made up the companies and stole half the surnames from Dickens. (OK, that and the belly button lint.)

Such articles have been a staple of workaday “financial journalism” for at least the past few centuries; they usually contain three elements:

1.   General assertions about the emotional state of the market, most commonly the distress of retail and/or institutional investors about recent losses or, during frothy periods, how the financial mood is “risk on” or, even more jaw grindingly, that “cash is coming off the sidelines.” (The latter defies simple accounting. If Bob pays Betty $1,000 for her stock, Bob’s $1,000 indeed came off the sidelines, but Betty just sent her $1,000 back to the sidelines.)

2.   The portfolios and transactions of uninformed small investors and the pleasure, pain, frustration, and triumph they experience in the process.

3.   The observations of professional money managers and market strategists, whose forecasting skills rank somewhere between a cuckoo clock and a ham sandwich. After all, if they really could predict market direction or pick stocks, they wouldn’t be giving their calls and picks away for free in a national publication.

In 1998, the personal finance writer Jane Bryant Quinn published the seminal criticism of the swamp of modern financial reporting in the Columbia Journalism Review. She famously described its content as “financial pornography”: investment coverage that perpetuates the myths and false promises of stock picking, market timing, and asset allocation fairies.

Quinn had a lot more on her mind than small investors and brokerage BS artists. She began by identifying the financial press’s fixation on celebrityhood:

Many business journalists, I fear, have left home and joined a cult. Our Bo and our Peep are Buffett and Gates. We hang on their words as if they are wise. . . . We are entranced.

Warren Buffett’s face has been instantly recognizable for more than three decades (and in the past decade has been transmuted into the planet’s mother lode of clickbait). Gates’s image, on the other hand, has been replaced by those of more recent industrial heroes: Elon Musk and Mark Zuckerberg, to name two. For our purposes, the most important genre of financial celebrity porn is the star money manager, beginning with Gerald Tsai and continuing through Michael Kassen and Bill Miller, all the way to today’s Cathie Wood, who has become a daily presence in print, on cable TV, and online.

Quinn’s article identified the financial press as part of an ecosystem of “predators and prey” in which

When we [the financial press] go with the flow, embracing the predator’s point of view, we sometimes unwittingly become predators ourselves. You know the stories: The Top Ten Mutual Funds to Buy Now, How to Double Your Money This Year, personality profiles that read like fan magazines. Stock-touting pieces that praise any path to profits. We’ve all done these stories, in one form or another. It’s investment pornography—soft core, not hard core, but pornography all the same.

Quinn ended with this cri de coeur:

But what is our responsibility to readers, when we become stock salesmen, too—directly or indirectly? How do we cover this gold rush at arm’s length, if we join it rather than observe? How do we report on this astonishing rush to get rich without glorifying attitudes that may be destructive and cannot last?¹

The answer is that financial journalists can’t, for the simple reason that there are only so many ways a reporter can tell investors to buy and hold index funds.

Have mercy on the investment writer with a mortgage and student loans who must crank out copy every day. In 1999, an anonymous piece appeared in Fortune titled “Confessions of a Former Mutual Funds Reporter.” Its writer admitted, “By day we write ‘Six Funds to Buy NOW!’ We seem to delight in dangerous sectors like technology. We appear fascinated with one-week returns. By night, however, we invest in sensible index funds.” The piece continued, “We were preaching buy-and-hold marriage while implicitly endorsing hot fund promiscuity.” Why? Because, “Unfortunately, rational, pro-index-fund stories don’t sell magazines, cause hits on web sites, or boost Nielsen ratings.”²

Beyond avoiding starvation, a web of corruption entangles financial journalists and the finance industry: advertising. The financial service business is the nation’s third-largest industry, and it is both print and electronic media’s single largest source of advertising revenue. Given the parlous state of both print and online journalism, financial publications can hardly afford to offend their biggest rice bowl.³

Is any financial journalism worth reading? Almost none. Jason Zweig at The Wall Street Journal has a superb grasp of both evidence-based finance and neuroeconomics, and a few columnists at The New York Times, such as Jeff Sommer, Tara Siegel-Bernard, and Ron Lieber, also adhere to Quinn’s standards.

But on the whole, investors are better off ignoring not only both these publications, but nearly all financial print media. Among general audience publications, only one consistently conveys a nuanced, cutting-edge approach to finance, and that’s the Economist. The magazine’s more than a bit pricey and its tiny print requires either young eyes or an operating microscope. The Financial Times is also sometimes worth reading, but its digital library availability is embargoed for a month, and accessing the current issue, at several hundred dollars per year, is not cost efficient for many.

If the financial print media is a swamp, then the financial electronic media is a sprawling sewage plant, headquartered at CNBC. If it’s impossible to write a new and useful personal finance piece five days a week, the task of coming up with a dozen hours of relevant cable TV financial content every day boggles the mind.

Before the 1990s, financial television was a backwater. Besides PBS’s Wall Street Week and Nightly Business Report, few in the media saw much potential in conveying the ins and outs of stocks and bonds onto the tube, a conclusion confirmed by the failure of the Financial News Network (FNN), founded in 1981 and bankrupted in 1991. It then fell into the hands of NBC, which rebranded it as the Commercial News and Business Channel (CNBC).

In 1993, Roger Ailes arrived at CNBC, then at the apex of his legendary grasp of television’s raw emotive power. The combination of hemophilia and a physically abusive father blighted his childhood and punctuated it with frequent bleeding episodes and long periods of home confinement; 1950s television became his classroom. At Ohio University he majored in media studies. He cut his teeth on production work at local television stations before he embarked on a quarter-century career in media consulting for Republican presidents, making Nixon more likable in 1968 and in 1988 helping George H. W. Bush defeat Michael Dukakis with Lee Atwater’s vicious “Willie Horton” ads.

Upon arriving at CNBC, Ailes applied the lessons he’d learned in political advertising to overhaul every aspect of the look and feel of the network. Instead of simply announcing a news segment with theme music, he added voiceovers with tight head shots of the anchors. He personally instructed camera operators on how to properly frame corporate executives to make them appear more alive, prodded writers to come up with more compelling “don’t touch that channel” patter, and sent anchors to breathlessly report the price action from the floor of the stock exchange. The more flamboyant the guest, the better. As the New Yorker’s John Cassidy wrote:

Their ideal studio guest was a former beauty queen who covered technology stocks, spoke in short declarative sentences, and dated Donald Trump. Since there weren’t many of these women available, the producers generally had to settle for balding, middle-aged men who revered Alan Greenspan and tried their best to speak English.⁴

Ailes single-handedly transformed finance into a spectator sport. He intuitively understood that his audiences preferred the cotton candy of entertainment to the spinach of information and analysis. The best confection of all was one that spun unlimited wealth. He also married sex and finance by making a new recruit from CNN, Maria Bartiromo, an anchorwoman. Her Sophia Loren looks, dense Brooklyn accent, and blatant sex appeal transformed her into “the Money Honey.”⁵

Under Ailes, CNBC mastered that genre and perpetrated a feat of modern cultural alchemy by transmuting the tedious world of mainstream finance into wildly successful entertainment. The new venue’s attention centered on the internet, which small investors could then use to trade on the “information” they inhaled on CNBC.

How well does this work for investors? About as well as you might expect. One academic study examined the reaction of stock price to the appearance of corporate CEOs on CNBC, while another researched the performance of the stock picks of the hyperkinetic, wildly popular Jim Cramer on his Mad Money show. I’ve displayed the results of both studies in Figure 15.1, which show pretty much the same thing: a price bump relative to the rest of the market that peaks on the day of or the day after the show airs, followed by a price fall.⁶

FIGURE 15.1 Effect of CNBC CEO interview and of Mad Money stock mention

The price fall after the show is discouraging enough, but the rise beforehand suggests something more sinister—that participants with foreknowledge of the show’s schedule of guests play CNBC’s viewers like two-dollar banjos. Despite his clownish appearance, Cramer is no dummy and well understood this dynamic. On at least one occasion he sold stock in a company touted on Bartiromo’s show, then bought it back a few days later after its price drifted back down.⁷

WHAT ABOUT SOCIAL MEDIA?

Modern social media is for the most part an echo chamber time suck, although if you’re extremely careful and lucky, Twitter is often the first place that useful financial concepts and data see the light of day. In general, though, the odds of finding useful information on this 280-character platform are approximately the same as those of finding a Higgs boson under your sofa. Avoid TikTok, which seems almost exclusively aimed at the very young and uninformed. The same will probably go for whatever platform has come into fashion by the time you read this. Look elsewhere.

WHAT SHOULD I READ, WATCH, AND LISTEN TO?

The sorry state of financial print and media journalism suggests that you shouldn’t waste much of your precious financial bandwidth on newspaper financial pages, on social media, or God forbid, on cable TV. There are some exceptions to this, as mentioned earlier, the Economist and The Financial Times.

If you’re extremely careful, the internet does serve up some useful sites, prime among which is the discussion board and wiki pages at bogleheads.org, as well as Jonathan Clements’s superb humbledollar.com, both of whose well-informed content and civil environment are the result of expert moderation.⁸ Investopedia.com is another authoritative reference site.

YouTube also contains a treasure trove of lectures by nearly all of finance’s leading lights, strewn throughout its vast wasteland of misinformation. Tread carefully. A few wrong clicks and you’ll wind up with a QAnon conspiracist or a crypto bro. Of the names I’ve mentioned in this book, I’d search for John Bogle, Eugene Fama, Kenneth French, Jonathan Clements, Zvi Bodie, William Sharpe, Burton Malkiel, Charles Ellis, and Jason Zweig.

Worthwhile finance podcasts abound. Start with the Economist’s weekly “Money Talks” and NPR’s Planet Money, although most of the latter’s superb coverage revolves around economics and relatively little around investing. Rick Ferri’s Boglehead podcast interviews cover mainly passive investing. Another financial podcast I highly recommend is Barry Ritholtz’s Masters in Business from Bloomberg. Podcasts are a rapidly evolving area. Lest you wear your ears out, you’ll need discretion to curate the burgeoning amount of high-quality audio.

Research mutual funds. All the fund companies discussed in this book have sophisticated websites from which basic fund facts, such as fees and expenses, can be obtained, as well as annual and semiannual reports that list and tabulate holdings.

If you’re researching a large number of funds, this gets cumbersome. The best way is to visit Morningstar.com. Use the site’s search function to locate the main page for the fund you’re interested in and click the “Expense” and “Portfolio” tabs to find the fund expense ratio and detailed data on the fund holdings. Click the “Performance” tab to see the fund’s return over periods ranging from a single day up to 15 years, and the “Chart” tab to compare the returns of multiple funds over a given interval.

***

Best of all, pretend it’s 1989 and read books. Here’s where I’d start:

Images   Financial theory. John Bogle’s Common Sense on Mutual Funds and Burton Malkiel’s A Random Walk Down Wall Street are the two go-tos. If (and only if) you get bitten by the finance bug, hit the classics: Irving Fisher’s The Theory of Interest and Benjamin Graham’s The Intelligent Investor, and maybe even Graham and Dodd’s full monty, McGraw-Hill’s 2002 reprint of the classic 1940 second edition of Security Analysis.

Images   Financial history. I recommend two by Ed Chancellor: Devil Take the Hindmost, his nonpareil romp through bubbles and panics, and The Price of Time, a beautifully written history of finance from Babylon to Bezos. As frosting on the Chancellor cake, inhale Fred Schwed’s Where Are the Customers’ Yachts?, which will alternately teach you how little has really changed in investing and make you laugh out loud. John Kenneth Galbraith’s A Short History of Financial Euphoria rounds out the list of highly entertaining financial history romps.

Images   Financial psychology. Jason Zweig’s Your Money and Your Brain, Morgan Housel’s The Psychology of Money, and Jonathan Clements’s How to Think About Money are all excellent. (Full disclosure: I wrote the foreword to Clements’s book.)

Images   Financial business. Read Helaine Olen’s Pound Foolish and License to Steal, written by Timothy Harper and an anonymous broker. The latter should be read only on an empty stomach.

Images   Putting it all together. The Bogleheads’ Guide to Retirement Planning supplies an invaluable road map to your investing career. Physicians should read emergency room doctor Jim Dahle’s White Coat Investor. Even better, give it to your kid before she goes to med school.

CHAPTER 15 SUMMARY

Images   Turn off your television.

Images   Avoid newspapers’ financial pages.

Images   Spend most of your energy on books by the reputable authors I’ve mentioned. Be careful when you peruse Amazon.com or your local bookstore; it’s a jungle out there. For every Bogle, Malkiel, and Chancellor, there are a thousand charlatans.

Images   Read the Economist’s finance section.

Images   Listen to podcast interviews of reputable finance academics or find their lectures on YouTube.

Images   Avoid interviews with corporate executives, market strategists, and portfolio managers.

INVESTMENT STRATEGY

Assembling the Four Pillars

THE WINNER’S GAME

Our voyage through the theory, history, psychology, and business of investing finally pays off in this section, where we assemble these four pillars into a coherent investment strategy that you can deploy and maintain with a modest amount of effort.

First we’ll explore the retirement “numbers game”: How much will I need to save to meet my goals? How much can I spend? How certain can I be of success? In Chapter 17, we reach the book’s “main event”: What factors must I consider in designing my portfolio? Just what should my portfolio look like? What funds do I buy?

I lay out practicalities in Chapter 18. The first part is your portfolio’s assembly instructions. It illustrates a practical method for the psychologically tough task of slowly building your stock exposure. The second section is the maintenance manual. It describes the periodic “tune-ups” necessary to maintain your portfolio’s health.

With apologies to Winston Churchill, by the end of this section you will not have reached your investment journey’s end; you will not even reach the beginning of its end. But you will have ended its beginning and, more important, will possess the road map for the rest of the journey.

CHAPTER 16

HOW MUCH DO YOU NEED TO RETIRE?

Or, Why You Shouldn’t Use a Retirement Calculator

Retirement saving and spending are much the same as achieving your career and family goals. While both follow some general rules, the vicissitudes of life and the financial markets make even approximate forecasting impossible. The hardworking and analytical person is more likely to succeed than someone who isn’t, but occasionally a lazy fool can fall into a cushy lifetime sinecure, or contrariwise, a reliable and brilliant 60-year-old employee can despite his best efforts find himself at a bankrupt company with a shrunken pension.

Retirement finances can be just as capricious. Certainly, the more you save during your working career and the lower your burn rate in retirement, the more likely you are to succeed. But the improvident spender can still luck out with a favorable sequence of returns (low during saving, high in retirement), and the disciplined retiree may experience the reverse returns sequence. In addition, everyone is subject to the risk of expensive personal or societal disasters.

Such investment uncertainties are enormous, and I stay away from retirement calculators because they ignore the caprice of human existence in all its fullness and thus provide a false sense of security. With a high enough savings rate and a low enough burn rate, it’s possible to get almost any online or software retirement planner to spit out a 90% or 95% success probability, but you don’t need an Ivy League history degree to realize how silly this is. The Roman Empire lasted only about a half a millennium, so the average person with an 85-year life expectancy has a roughly 15% chance of encountering a society-wide collapse; moreover, no one lives in a trouble-free era. Even worse, many online calculators assume that future stock and bond returns will be as generous as in the past, a forecast whose likelihood ranks somewhere between that of Santa Claus and the Easter Bunny.

Given all this uncertainty, how to proceed? Start with a back-of-the-envelope calculation to get you into the ballpark, then understand just how huge that ballpark is. First calculate your annual residual living expenses (RLE), which are your spending needs beyond your Social Security and pension checks. Plan and work to accumulate approximately 25 years of that RLE. Next, calculate how much you need to save to get there. Finally, bracket that estimate with a large amount of uncertainty by at least a factor of two in both directions.

To see how that works in the real world, recall Chapter 6’s Fritz. To recap, he’s a 65-year-old recent retiree whose living expenses and taxes are $50,000 per year, $20,000 of which is covered by Social Security and pensions. This leaves him an RLE shortfall of $30,000 per year, so he’ll need 25 × $30,000 = $750,000 to retire.

The $30,000 and $750,000 figures are in today’s dollars and pegged to the moment he retires. If inflation averages 3%, in 24 years, at age 89, he’ll be spending $60,000 per year in nominal dollars (remember the “rule of 72” for doubling, i.e., 24 × 3 = 72). It’s thus important to estimate returns assumptions in postinflation terms. Realize just how approximate that $750,000 suggested nest egg is. If Fritz lucks out with high returns in his retirement’s first decade, he’ll need far less than $750,000; if the opposite occurs, he’ll need a lot more. If he has an expensive illness, an extended nursing home stay, or both, he’ll need a whole lot more. While $750,000 might be nice, a cool million or two would be better. When all is said and done, Fritz just doesn’t know with any precision how big a nest egg he’ll actually need.

Once we’ve got a target amount for Fritz’s nest egg, we work backward to figure out how to get there. Fritz began working in the early 1980s and accumulated his $750,000 nest egg with ease because of the subsequent anomalously high stock and bond returns. Today’s savers will likely face lower future returns and thus will have a steeper climb.

To deal with the fall in expected stock and bond returns, let’s switch gears to Fritz’s niece Felicia, who started her working career in 2023. How should she save and invest to amass $750,000 in today’s dollars in 40 years? Let’s assume she makes an inflation-adjusted $70,000 per year. How much of her salary should she contribute to her 401(k) plan?

Monthly Savings Required to Accumulate $750,000 in 40 Years

This table is the financial life-cycle equivalent of the famous Dirty Harry line, “You’ve got to ask yourself one question: Do you feel lucky?” I’ve estimated the future real return of a 60/40 portfolio at close to 3%, but the confidence limits of that estimate are wide. A 60/40 portfolio has an annual standard deviation of around 9%, which annualized out to 40 years is 1.4% per year Images. This means that 95% of the time, the realized inflation-adjusted return over four decades will be between +0.2% and +5.8% (3% plus or minus [2 × 1.4%]).*

The 95% confidence limit of expected portfolio return only scratches the surface of the savings question’s uncertainty. Excel’s PMT function assumes constant portfolio returns, but in the real world, sequence matters. As a young saver, Felicia wants a sequence of bad returns followed by good returns, whereas such a sequence just might bankrupt her retired uncle, who wants the good returns in his initial retirement years.

The preceding paragraphs describe only the uncertainty of retirement planning served up by the finance gods. Felicia’s career could take off and put her on retirement easy street, or she could contract a disabling illness or find herself in a dead-end job or with a recently obsolete work specialty. She just doesn’t know.

Even if her projections of salary, taxes, and living expenses turn out to be accurate, her savings rate will be anything but constant, particularly during the years she and her spouse are paying for day care, private education, and college tuitions, so the savings amounts in the preceding table constitute at best only a rough lifetime average.

Only one thing is certain: she’s going to have to put aside a lot of money. Even at an optimistic 4% real return, she still must save an average of 10% of her pretax salary starting at age 25. If she doesn’t pay off her student debt and begin saving until age 35, her required savings rate at a 4% real return increases to 18.5% of her pretax salary; at a 2% real return, it’s 26% of her salary. If her portfolio return is lower, her retirement prospects dim yet more.

***

Even if you can invest like Warren Buffett or James Simons, it won’t do you any good if you can’t save. Our consumer society propels the average person to spend far more than is necessary or healthy. If you find it difficult to save, you have a problem.

In The Millionaire Next Door, Thomas Stanley and William Danko describe how most people become rich. Want to know the auto most commonly driven by the wealthy? No, not a Mercedes—it’s a Ford F-150 pickup. Another interesting fact: the average plumber retires sooner than the average lawyer, even though lawyers make more money than plumbers. Why? Because the attorney must spend more than the plumber to keep up with his cohort of Joneses, so he typically drives a nicer car, lives in a nicer part of town, buys more expensive clothes, and takes more exotic vacations.¹

Like any other economic phenomenon, wealth accumulation is a complex process with numerous contributory causes beyond frugality. Even so, if you can’t save, you’re far less likely to get rich.

OTHER GOALS

This book is not intended as a financial planning guide. Topics such as mortgages, debt management, insurance, and estate planning are well beyond its brief. But it’s worth mentioning a few planning topics pertaining to basic portfolio mechanics and financial theory:

Emergencies. What constitutes an “emergency fund” depends on your age and employment status. A twentysomething who works for the government probably needs no more than 6 months’ savings. If your job security is tenuous and you might need further schooling to find another job, then put a year or two’s living expenses in the bank.

On the other hand, the retiree with zero remaining human capital needs at least 10 years of RLE in safe assets. That’s not as bad as it sounds, since the fixed-income part of the nest egg provides a reliable emergency stash. For example, Fritz’s portfolio has 25 years of RLE. At a 60/40 stock/bond ratio, he owns the required 10 years of Treasuries and CDs.

If you’re young, keep your emergency money in your taxable accounts, as tapping an IRA before age 59½ for an emergency will likely trigger a large combined tax bill and early-withdrawal penalty. Under certain circumstances you can begin to withdraw from an IRA at age 55 under IRS Rule 72(t), which involves a schedule of periodic withdrawals, as well as from a 401(k) plan. Many employer retirement and 401(k) plans allow borrowing in emergency situations. This is a bad idea, since defaulting on such a loan triggers a 10% early-withdrawal tax penalty. This is especially likely to happen if your emergency cascades into losing your job, which will require that you immediately pay back the loan. You should consult your accountant before considering any of these strategies.

House savings. If you plan to buy a house within five years, you should also place this money into short-term bonds, CDs, and money market accounts. Keep it in a taxable account.

College savings. This is an area that has undergone a revolution with the introduction of 529 plans, which are tax-advantaged. Look at www.collegesavings.org and chat with your accountant about these plans.

From the asset management point of view, college savings is a sticky wicket, since its time horizon is between that of emergency savings and retirement planning. You may be saving for a few years or two decades, depending on your child’s age and your available funds. Unfortunately, stocks can have poor returns for even 20 years. If you have a decade of subpar returns, you will find yourself well within the five-year “bond only” window. If you begin saving when your son is four and have nine years of bad returns, you have five years left until he enters college. What do you do? With some trepidation I’d recommend placing a maximum of 30% to 40% of his college fund in stocks, then gradually shifting that into bonds as matriculation approaches. When the college expenses come due, you can sell the residual stocks for tuition in the good years and sell the bonds in the bad years.

CHAPTER 16 SUMMARY

Images   Aim to accumulate at least 25 years of residual living expenses: your living expenses in excess of your Social Security and pension income.

Images   Keep it simple: use Excel or a financial calculator—either a handheld device or an online version such as the one at smartasset.com/investing/investment-calculator—to get into the savings target ballpark, then realize just how big that ballpark is.

Images   Do not rely too much on online or software retirement calculators, which often contain unrealistic returns assumptions and underestimate the risks inherent in the human condition. At best, treat their outputs as only the roughest of estimates.

* For this calculation, use Excel’s PMT function. In this calculation, if we assume Felicia earns a 2% real annualized portfolio return, the formula for the required monthly savings is = PMT(0.1667%, 480, 0, 750000, 0), where 0.1667% is the simple monthly rate on an annual 2% return, 480 is the number of months in 40 years, 0 is the starting value, 750,000 is the ending value, and the 0 indicates that payments are made at the end of each month (1 if the beginning of the month). The required monthly savings appears as a negative number, in this case, −$1,021.10.

CHAPTER 17

BUILDING IT, MAINTAINING IT, AND SPENDING IT

Investing is an operation that transfers wealth to those with a strategy they can execute from those who don’t or can’t. It’s time to construct it. You’ve already learned everything you need to know:

Images   The risk and return of asset classes

Images   The possible impact of value stocks’ higher returns, plus how stocks respond to inflation

Images   The rationale for passive management

Images   The theory of portfolio construction

Images   The allocation of assets over your life cycle

Images   The need to combine different asset classes into prudent portfolios

All that remains is the assembly of your portfolio, one piece at a time, and its maintenance.

Similar to building a house, you’ll assemble your portfolio from different materials—the bricks, timbers, and shingles—that correspond to the three main kinds of investments: US stocks, foreign stocks, and short-term bonds/cash. Each comes in different wrappers: open-end funds, ETFs, and individual Treasury bills and notes. The exact nature of the wrappers matters far less than what’s inside them. Whether you use an ETF or an open-end fund for a particular stock asset class matters little, and the decision to purchase a Treasury bond fund versus building your own Treasury ladder simply trades off cost and convenience, as the ladder saves you the mutual fund fee but takes a modest effort to maintain.

Next, we’ll discuss which asset classes are most appropriate for the metaphorical house you are building. Just as you would favor wood over steel beams and concrete for building a small residence, so too are certain asset classes and mutual funds more appropriate for certain kinds of portfolios.

To complete the analogy, the ultimate purpose of your portfolio, just like your house, is to protect you from the unpredictability of the elements. When you build a house, you cannot accurately forecast exactly which force of nature will most likely threaten it. If you knew in advance whether flood, fire, or storm would strike, then you could design it more precisely. But you never know what Mother Nature will actually deliver, so you compromise to minimize the damage from all possible threats within your construction budget.

In the same way, you cannot know exactly what kinds of economic, political, or even military adversity will befall your portfolio. If you knew for certain that inflation would rampage during the next generation, for example, then you would emphasize natural resource stocks, real estate, TIPS, and cash, as well as a fair amount of value stocks. If you knew we were to suffer a deflationary depression similar to that experienced in the 1930s, you would hold a large amount of long-maturity Treasury bonds. If you knew the world would suffer a catastrophic loss of confidence in US industrial leadership, you would want a portfolio heavy in foreign stocks.

Over the decades of your investing career, you will wish that you had owned what turned out to be the best allocation, but today you can’t know what that allocation will turn out to have been. The safest course is to design a portfolio that will protect enough of your wealth to keep you out of harm’s way under most circumstances. This avoids the catastrophe of holding a portfolio concentrated in what turns out to be the worst asset classes—for example, a portfolio loaded with long-maturity nominal bonds during a period of hyperinflation.

In Chapter 14, we reviewed one of the most influential finance articles ever published, Charles Ellis’s “The Loser’s Game,” which provided some of the inspiration for the launch of Vanguard’s first index fund.¹ Ellis observed that investing was like amateur tennis. The most common way players at this level lose is through “unforced errors,” such as missing easy shots and trying to nail the corner. The best way to win a game with your friends is simply to safely return the ball. The investing equivalent of trying to nail the corner is a portfolio that aims for the highest possible returns with an asset allocation concentrated in one area, such as tech stocks. Don’t do it. Win with the investing equivalent of lobbing the ball over the net by building a highly diversified portfolio, which will never shoot out the lights, but which minimizes the odds of making you poor. In this chapter, we’ll do that.

A winning portfolio strategy can be as simple as a single broadly diversified mutual fund that holds a prudent mix of global stocks and bonds, such as a target-date retirement fund (or one of Vanguard’s Life Strategy Funds), or one as complicated as that mentioned toward the end of Chapter 7, which owned 10 different stock asset classes.

To better understand this process, we’ll consider fictional twentysomething triplets: Yvonne, Yvette, and Yolanda.

Yvonne works at a large corporation as a graphic designer, doesn’t like math, and couldn’t care less about finance. She’s pleased that her company’s 401(k) offers a wide selection of low-cost indexed target-date funds; the less she has to think about her retirement account, the better. The plan’s brochure (and finance theory as well) suggests that her age points to the 2065 fund, which has an 89% stock allocation.

The trouble is, Yvonne has never been through a bear market, and her worst-case investment scenario is a severe one that shocks her out of a prudent long-term investment strategy. To avoid that, she should start out with an approximately 60/40 stock/bond mix. The Vanguard 2030 fund, at 64/36 stock/bond, has close to that allocation. With a relatively conservative portfolio for her age, Yvonne can better gauge how she responds to severe market declines. If one occurs five years later and she sails through it, at that point she can put both her current holdings and future contributions into a more aggressive fund. But if the market fall upsets her, she should at least try to stay the course. If she can’t manage even that degree of fortitude, then she should switch her future contributions to a yet more conservative target-date fund.

If Yvonne is frugal and fortunate enough and has surplus cash after maxing out her 401(k), she can invest those funds the same way in an individual IRA and if she maxes that out, she can invest the same way in a taxable account.

Her sister Yvette works in accounting. She’s good with numbers and likes dealing with money, so she wants a more hands-on experience. She selects one of the modestly complicated asset allocation strategies and a 60/40 stock/bond ratio, with the following contribution amounts. (She would have preferred that the bonds be in a safer short-term Treasury fund, but the company plan doesn’t offer one, so she picked the next best choice, a short-term bond index fund.)

Images   39% US Total Market

Images   15% International Developed Market

Images   6% Emerging Market

Images   40% Short-Term Bond Index

The stocks in this allocation are 65/35 domestic/foreign (i.e., 39%/21% of the overall portfolio). There’s nothing magical about this domestic/foreign ratio. If you feel particularly strongly about the current cheapness of foreign stocks, you might want to increase the international allocation as high as 55/45. Contrariwise, if you’re uncomfortable with significant foreign exposure, you may want an 80/20 split. In the long run, your precise allocation matters far less than your ability to stick with it.

Because of normal random market fluctuation, after a while this allocation will get out of whack. At the end of every even-numbered year, Yvette rebalances the portfolio back to the target allocation policy weights. (Many 401(k) plans offer an automatic rebalancing feature; most plain-vanilla brokerage accounts do not.) If the inevitable severe bear market doesn’t faze her, she can proportionately increase the stock allocations of both her existing holdings and future contributions.

The third triplet, Yolanda, is part owner of a small, prosperous software development firm, and she’s mathematically gifted and thus fascinated by the academic finance principles discussed in this book. With a little help from her parents, she got into investing when she was young and ignores stock market losses with ease. As frosting on her cake, she’s doing very well indeed and socks away $100,000 per year: the $22,500 limit into her firm’s 401(k) plan, and the rest into a taxable account. (The preceding contribution limit increases annually with inflation; the $22,500 figure is for 2023.)

She’s chosen the 80/20 version of the complex and small/value-tilted portfolio in Chapter 7:

Images   30% US Total Market

Images   10% US Small Value

Images   8% REITs

Images   2% Energy Stocks

Images   2% Precious Metals Stock

Images   8% European Market

Images   8% Pacific Market

Images   4% Developed Market Small Value

Images   6% Emerging Market

Images   2% Emerging Market Small Value

Images   20% cash, short Treasuries, and bond funds

Rather than simply contribute her inflows to these funds according to their policy weights and then periodically rebalance, Yolanda deploys a mathematically complex accumulation method called “value averaging,” first described by Harvard professor Michael Edleson in a book with the same title. (Full disclosure: I wrote the Introduction to this book’s paperback edition.)

The typical 401(k) plan deploys dollar cost averaging (DCA), which adds the same amount every quarter to a given asset class: perhaps a total of $1,000 to US stocks. Value averaging instead targets the actual dollar amount in the account. In the simplest deployment of value averaging, the goal is an increase of $1,000 per quarter, so that at the end of succeeding quarters, the investor aims to have $1,000, then $2,000, then $3,000, then $4,000, and so forth, in US stocks. If US stocks do well in the preceding quarter, the investor adds less than $1,000 to meet the target. If they do poorly, the investor adds more than $1,000.

This explanation oversimplifies the process, since stocks have a positive return over long periods of time. Edleson adjusts for this by increasing the target amount by the expected return of the stock asset class. Let’s say that we assume that the long-term return of stocks is a nominal 7%. We add the $1,000 to the preceding quarterly amount, then multiply that total by 1.0171 (the fourth root of 1.07); the target amounts in the preceding paragraph thus become $1,000, $2,034, $3,086, and $4,156.

Table 17.1 shows what the first three years of the equity side of Yolanda’s value averaging path look like.

Table 17.1 Yolanda’s Value Averaging Path

USTSM = US total stock market, USSV = US small value, REIT = real estate investment trust, ENER = energy stocks, PME = precious metals equity stocks, EUR = European stocks, PAC = Pacific stocks, ISV = international small value, EM = emerging markets, EMSV = emerging markets small value

Value averaging is an effective technique for deploying a stream of savings into a portfolio, but it isn’t perfect. If there is an especially severe global bear market, on a par with the 2007–2009 downturn, Yolanda will consume all the cash and bonds in her portfolio long before the three years in Table 17.1 are up. The opposite will happen if stock prices rise dramatically, in which case she’ll add less to stocks each period than she would by making fixed contributions to each asset class, and wind up with a stock allocation below the 80% target.

That said, value averaging has many strengths as an investment strategy. It forces the investor to invest more at market lows than at market highs and produces higher returns under most circumstances. It gives the investor the experience of investing increased sums in stocks regularly during times of market pessimism and fear—a valuable psychological ability. Unlike dollar cost averaging, value averaging mandates investing larger amounts of money at market bottoms than at market tops. You can think of value averaging as a combination of DCA and rebalancing.

Yolanda has a roughly 80/20 split of taxable and tax-sheltered assets. Her sheltered 401(k) should hold all the REITs, since most of their return comes from nonqualified dividends taxed at the full marginal rate. Especially during the early years of her saving career, rebalancing will be accomplished automatically with the discipline of value averaging and will demand little or no selling because of the relatively large savings inflows. In later years, she should try to hold most of the more volatile asset classes, such as emerging markets, precious metals, and energy equity, on the sheltered side, as well as a bit of each of the other asset classes in her 401(k), to accommodate tax-free rebalancing. Also in later years, her asset allocation policy may tell her to sell some of the most appreciated stock assets, which she may want to defer to avoid paying capital gains taxes. Because her two sisters will have most of their savings in tax-free accounts, they don’t have the problem of capital gains mandated by rebalancing selling.

If the triplets set up both traditional 401(k) and Roth 401(k) accounts, they should split their contributions between the two as a form of “tax diversification,” since they can’t predict whether future marginal tax rates in retirement will be higher or lower than now, which would advantage (respectively) the Roth and traditional accounts.

TAXABLE TED’S DILEMMA

Ted’s life was that of an entrepreneur. He founded a firm specializing in satellite components, where a punishing succession of 80-hour weeks punctuated by labor troubles, parts shortages, incessant travel, and payroll squeezes consumed him. After a quarter century of this, he gratefully accepted a seven-figure buyout from a larger competitor.

Ted’s sitting on a large wad. He’s got a small IRA and even smaller personal savings, and he never had the time to set up a company pension plan or even a 401(k). What should he do with all that money?

Ted successfully invested his tiny personal savings through both the dot-com collapse and the 2007–2009 financial crisis. He’s read, absorbed, and put into practice the books of John Bogle and his acolytes, particularly the Bogleheads’ Guide to Investing, so he knows exactly how he wants to proceed: a simple “three-fund portfolio” with one-third each in Vanguard Total Stock Market, Vanguard International Stock Index Fund, and Short-Term Bond Index Fund.*

With serious money sitting in his bank account, Ted now faces a dilemma. Does he take a deep breath and deploy it all at once into his three-fund portfolio, or does he do it gradually over a period of time? The former course is known as “lump-sum” investing, whereas the latter can be done either with the DCA used by the typical 401(k) participant or Yolanda’s more complex value-averaging technique.

DCA is popular because of the following paradigm: Imagine that the price of a stock or of a market bounces among $5, $10, and $15 per share, with an average of $10 per share. If you invest $30 into each of these share prices, you’ll buy 6 shares at $5, 3 shares at $10, and 2 shares at $15, for a total of 11 shares totaling $90, for an average price of $8.18, instead of the $10 average price.

Magic, right? Unfortunately, this DCA parable ignores the fact that over time, stocks rise in price. Deployed over periods of longer than a year, lump sum beats DCA most of the time.²

But this supposed superiority of lump-sum investing over DCA is deceptive, since the higher return comes at the cost of higher risk. By definition, all the lump-sum amount is invested in stocks, whereas on average only half the total DCA dollar asset pile is. (If you invest $1,000 using DCA over the course of a year starting at zero, during that period you’ll have an average of roughly $500 exposed to the stock market.)

The math part of the lump-sum versus DCA/VA conundrum is ambiguous, but the Shakespeare part isn’t. Both DCA and value averaging minimize the regret felt by the person who chose to invest a lump sum at an inauspicious time, such as at the market top of 2000. That unlucky investor suffered two severe bear markets and overall negative returns over the ensuing decade. In an admittedly extreme case, the investor who dollar cost averaged $100 per month into the S&P 500 between January 2000 and December 2009 would have seen their total $12,000 investment grow to $14,123, whereas the person who invested that $12,000 lump sum on January 1, 2000, would have only $10,909 ten years later.

The French philosopher Blaise Pascal defended his belief in God like this: Suppose that God does not exist. The atheist “wins” and the believer “loses.” If God does exist, the situation reverses. The consequences of being wrong with each belief, however, differ starkly. If God does not exist, the believer only loses the opportunity to fornicate, imbibe, and skip boring church services. But if God does exist, the atheist roasts eternally in Hell. The rational person (or at least one who believes that the Almighty cares how he behaves and what he thinks) thus chooses to believe in God.

As with Pascal’s wager, DCA and value averaging minimize regret. The investor loses with DCA and value averaging if market returns are high during the DCA/value averaging period, when he would have been better off with a lump-sum deployment. But that’s not as bad as having a lump sum slammed with a decade of returns like those between 2000 and 2009, to say nothing of 16 years of negative real returns, as happened after 1966. Lump-sum investing is an optimal technique you might not be able to face executing, whereas DCA/value averaging is a suboptimal technique that’s much easier on your psyche.

Finally, lump sum versus DCA/value averaging is not an either-or proposition. Ted can lump sum half of his portfolio assets and DCA/value average the rest over several years. During the late 1990s, while US large-cap stocks were grossly overvalued, most other stock asset prices were more reasonably priced. REITs yielded, for example, around 8%. In the late 1990s, it would have been reasonable to begin the US large-cap/total stock market allocation from scratch, but to start out more fully invested in less-expensive asset classes. Currently, foreign stocks are selling more cheaply than domestic stocks, so Ted might consider starting out his foreign stocks with a substantial lump sum.

Ted’s situation is unusual; for the average young investor in the savings phase of their investment life cycle, the lump-sum versus DCA/value averaging conundrum is irrelevant, since far more assets are invested in regular, periodic fashion than in a lump-sum fashion.

TO REBALANCE OR NOT TO REBALANCE

As a practical matter, during the early and middle portions of your savings career, under all but extreme market conditions, you’ll be rebalancing mainly with inflows. If an asset class does poorly relative to the rest of the portfolio, you’ll direct more of your savings stream to it to bring it up to policy. If an asset class does well relative to the rest of the portfolio, you’ll direct less of your savings stream toward it.

What about a mature portfolio with relatively small or no net inflows or outflows? Imagine that you have a $100,000 portfolio that is split 50/50 between stocks and bonds, and that over several years the stocks double in value, while the bonds’ value remains steady at $50,000. (This would happen with a rate increase that devalued the bonds’ principal value by the same amount as their cumulative interest stream.)

Your stocks have increased in value from $50,000 to $100,000, the bonds have stayed at $50,000, and the overall portfolio is now worth $150,000. To get back to your 50/50 policy, you’ll have to sell $25,000 of the stocks and use the proceeds to buy more bonds so that you have $75,000 of each.

Should you rebalance your portfolio? Some would answer “no” and point out that, for example, had you started out with a 50/50 portfolio of stocks and 5-year Treasury notes in 1926 and rebalanced annually until the end of 2021, your portfolio would have generated an 8.27% annualized return, and each dollar invested would have grown to $2,063 over the ensuing 96 years. But had you not rebalanced the portfolio, because of stocks’ higher returns, they would have gradually taken over the portfolio and would have compounded at a higher rate: an annualized 9.68%. Each dollar invested in 1926 would have grown to $7,094 by the end of 2021. (This sort of analysis is highly theoretical; because of investment expenses, taxes, spending, to say nothing of investor demise, no sentient being in this quadrant of the galaxy actually got those returns.)

Rebalancing hurt returns, but it also reduced risk, particularly in the later years. By the end of 2021, the portfolio would have consisted of 99.2% equity and 0.8% Treasuries, and your equity-heavy portfolio might have caused no small amount of insomnia during the teeth-rattling bear markets of 1974–1975, 2000–2002, and 2007–2009, and perhaps in 2022 as well.

In this example, the advantage of not rebalancing comes from the wide return disparity between stocks and bond returns. But sometimes rebalancing can boost returns. Recall the 50/50 S&P 500/REIT mix example from Chapter 4, where the annually rebalanced portfolio’s return was greater than that of either asset class alone, or the two-coin flip paradigm from earlier in that chapter, which had a return nearly a percent higher than a single coin flip. In both cases the returns of the two rebalanced assets were very close (S&P 500/REIT) or identical (two-coin flip), so rebalancing boosted returns.

Rebalancing a typical stock/bond portfolio will decrease return in the long run, but will also keep periodic losses down to a level you can live with and allow your portfolio to survive. Rebalancing among stock asset classes, which should have approximately the same long-term returns, may actually provide a small return boost to the equity side of your portfolio.

Beyond keeping your portfolio risk at a level you can live with and allowing your nest egg to survive and compound over the decades, rebalancing has another advantage: psychological conditioning. To realize a profit on any investment, you must buy low and sell high. Both of these things are hard to do, particularly buying low, which requires spending a large amount of your increasingly precious cash on an asset that has been falling rapidly. Further, battered assets are almost always accompanied by negative “expert” commentary. This is as it should be. Scary narratives always accompany low prices. Selling high means just the opposite. The asset you’re selling has had high recent returns and is outperforming other investments. The general consensus is likely to label the hottest companies the wave of the future. This also is as it should be. You don’t get high prices in any other way.

Rebalancing forces you to buy low and sell high. It takes many years and many rebalancing cycles for most investors to emotionally internalize that resistance to conventional wisdom. Think of the ability to move your portfolio against the crowd as your “financial condition,” by which I don’t mean how flush you are, but rather the strength of your investment discipline and the stability of your emotional balance. Like physical conditioning, financial conditioning requires its constant exercise. Periodically rebalancing your portfolio is a superb way of staying in shape.

The question of how often to rebalance is one of the thorniest in investing. Historical market returns favor rebalancing every two to five years, depending on what assets and what time period you look at. You have to be very careful in interpreting these data, because the optimal rebalancing interval is exquisitely sensitive to what assets you use and what years you study.

Rebalancing once every few years is likely optimal because of stocks’ differing long- and short-term behavior. If the markets were truly efficient, you wouldn’t be able to make a penny rebalancing among stock market sectors. After all, rebalancing is a bet that some assets (the worst past performers) will have higher future returns than others (the best past performers). We’ve already discussed stocks’ tendency to exhibit price momentum over periods of less than a year. But over periods longer than a year, that phenomenon reverses. At horizons of three to five years, the bulk of academic research shows a slight tendency toward mean reversion, with the best-performing asset classes doing worse going forward and vice versa.*

Keeping this in mind, don’t rebalance too often. An extreme example of the advantage of waiting is the behavior of US and Japanese markets in the 1990s. During this period, the US stock prices did almost nothing but increase, whereas the Japanese did almost nothing but go down. The longer you waited before selling US stocks and buying Japanese ones, the better off you were.

This discussion centers on calendar rebalancing—doing so on a specific date every year, two, or three. An alternative method is threshold rebalancing, in which you rebalance when an asset’s allocation exceeds a well-defined bound.

Let’s say that your target allocation to the total US stock market is 30% and that your rebalancing trigger is 25% of that. In that case, you’ll sell back to the 30% target when the allocation exceeds 1.25 × 30% = 37.5%. Security returns behave “lognormally,” which simply means that, for example, a 100% price increase and a 50% decrease both change the price by a factor of two. This means that you’ll buy the total US stock market when its allocation falls below 30%/1.25 = 24%. If you’ve designed your thresholds correctly, you’ll rebalance each asset class very roughly once every few years, which means that the thresholds should be higher for more volatile asset classes: 40% to 50% for emerging markets, for example.

Threshold rebalancing requires a fair amount of both effort and spreadsheet prowess. Because the rebalancing effect on return is so small, it’s statistically impossible to tell whether calendar or threshold rebalancing is superior. The former is certainly easier.

These considerations apply mainly to the tax-sheltered environment of retirement plans, such as IRAs and 401(k)s, where there are no tax consequences to rebalancing. Since rebalancing means selling the most highly appreciated asset classes, rebalancing taxable accounts generates substantial capital gains, particularly in older portfolios where fund shares were purchased long ago at much lower prices. Most investors have some combination of taxable and tax-sheltered accounts. Where you can, rebalance in the tax-sheltered accounts.

The most difficult rebalancing question applies to those who have large taxable and small or nonexistent sheltered accounts. Here you should rebalance largely with fund distributions and the selling necessitated by withdrawals.

DYNAMIC ASSET ALLOCATION

Dynamic asset allocation involves varying your policy allocation with changing market conditions. After spending much of this book convincing you of the virtue of fixed allocations, why am I relaxing this discipline so late in the game? Isn’t changing the policy allocation tantamount to market timing, a demonstrably profitless activity?

Chapter 11 described the pitfalls of using historical valuation metrics, such as the Shiller cyclically adjusted P/E ratio (CAPE), to adjust stock allocations up or down. Adhering to a fixed policy allocation with its required periodic rebalancing is hard enough. It takes years to become comfortable with this strategy; many lose their nerve and never see the thing through.

However, occasionally changing your allocation slightly in the opposite direction from very large changes in relative valuation can prove profitable. When I published The Intelligent Asset Allocator in 2000, relative stock asset class valuations were seriously out of whack. The S&P 500 sold at 30 times trailing earnings and the dividend yield was nudging 1%. Most other asset classes had grossly underperformed the red-hot S&P, some selling at near historically cheap valuations. I wrote:

If two years ago you thought that a 6% exposure to emerging markets was appropriate, perhaps with the recent carnage in this area 7% or 8% might not be inappropriate. If three years ago you were holding 40% S&P 500, perhaps 35% might not be a bad idea in the current bubbly environment.³

Around the time that I wrote that, I had the pleasure of a dinner with Mr. Bogle. I already knew that he expected US stock returns to be around zero because of a likely fall in valuations over the next decade. But I was also familiar with his iron determination to “stay the course” and never trade stocks based on economic conditions. So I waited for him to finish his martini and asked him if he had lowered his allocation to stocks. After a conspiratorial look around the room, he leaned in closer and admitted that he had reduced it by several percent.

Relative asset allocations today aren’t as extreme as they were back then, but over the past decade, the S&P 500 has once again outperformed and become relatively overvalued, while value stocks, particularly abroad, have underperformed and become relatively undervalued. It might be reasonable to adjust their allocations, respectively, down and up by a few percent from where they were several years ago.

Dynamic asset allocation gets a bad rap because most investors adjust their allocations in response to changes in economic or political conditions, a fool’s errand if ever there was one. Even the normal rebalancing process, which during severe bear markets can seem like repeatedly lighting your money on fire, requires nerves of steel and discipline. “Overbalancing,” that is, increasing/decreasing allocations after large falls/increases in price, involves even bigger and more discouraging purchases, and very few can carry it off. If you’re going to try it, make only small and infrequent changes in allocation, and even then only opposite to large changes in valuation.

SPENDING IT DOWN

Nearly all retirees should spend down their assets to delay Social Security to age 70. This can be a lifesaver for those with a high burn rate and is still a darn fine investment even if you’re Warren Buffett.

Beyond that, spending down always depends on circumstances. Retirees with a low burn rate, perhaps less than 3.5%, can simply maintain their long-term allocation with relatively little risk of running out. Above that spending level, stock allocations much greater than 50% are unacceptably risky.

In either case, you’re value averaging in reverse. Once you’ve established your asset allocation strategy, spending your portfolio down becomes an easy, intuitive process. As a practical matter, during periods of high equity returns, you’ll sell equities to hew to their allocation targets. During bear markets, you’ll spend down bonds.

FRITZ AND FRANK, AGAIN

The main issue you’ll face is whether and when to lower your overall equity allocation in retirement. This depends on three factors: your burn rate, your risk tolerance, and how you handle the trade-off between leaving bequests and maintaining your financial safety.

Recall Chapter 6’s Fritz, a retiree with a $750,000 portfolio and $30,000 per year in residual living expenses (RLE). He saved up 25 years of RLE, the inverse of which (1/25) yields a 4% burn rate.

A bad initial returns sequence combined with a 4% burn rate could extinguish any conceivable mixture of stocks and bonds by the time Fritz turns 80 or 85. No matter what his risk tolerance or bequest desires, he should aggressively protect his need for an inflation-adjusted stream of RLE. The essential first step in this process is spending down his retirement savings to delay receiving Social Security to age 70, but even the increased monthly payouts will not be adequate to completely cover his RLE.

He is left to choose between a TIPS ladder and a single premium immediate annuity (SPIA). The year 2022 saw a dramatic rise in TIPS yields, which make them attractive as of this writing. Their major drawback is that the longest bond, maturing in 30 years, would not provide for Fritz beyond age 95; in addition, there are no maturities between 2034 and 2039, although this problem will disappear over the next several years with successive 10-year TIPS auctions. Under normal circumstances an SPIA should protect against longevity risk, but in the event of severe inflation, that protection goes out the window as its initially generous payout turns into nominal funny money with each passing year. In addition to their inflation problem, an SPIA also bears the credit risk of the issuing company.

I would give the nod to the TIPS ladder; its longevity problem can be solved by buying a large amount of the 30-year bond, which at maturity can be converted to a shorter TIPS ladder or short-duration TIPS fund, whereas the inflation risk of an SPIA has no viable solution. (SPIAs can be bought with a fixed payout escalator, but this reduces the initial payout and is actuarially neutral to an SPIA without it. With high inflation, the escalator actually works against you, since its payout is tilted further into the future, which will suffer even more from the ravages of any inflation.)

Fritz’s cousin Frank, with a $3 million portfolio and the same $30,000 annual RLE requirement, has no such problem. His 1% burn rate protects him from all but a society-wide catastrophe, such as Armageddon, revolution, or environmental/natural disaster. He should still defer Social Security to age 70 simply because its inflation-adjusted 7.3% annual payout is a superb investment. Frank’s stock/bond split is constrained mainly by his risk tolerance. There’s no reason he couldn’t own an all-stock portfolio, since in all but a 1930s-style bear market, its dividend stream would more than cover his RLE. Most investors, though, don’t tolerate 100% equity exposure. Frank, who lived through the crunches of 2000–2002 and 2007–2009, has a pretty good idea of just how much equity exposure he can live with.

An important allocation consideration for Frank is his desire for bequests. No matter what his stock/bond allocation, his portfolio will long outlast his 1% burn rate, so in reality he’s managing most of his portfolio assets for his heirs, charities, and Uncle Sam, to whom he’s in fact rather grateful. If sleeping at night is more important than making his spendthrift nephews rich, he may want a more conservative stock/bond allocation, but if he wants to underwrite a new library wing, he’ll want to be more aggressive.

CHAPTER 17 SUMMARY

Images   Investment success revolves around a clearly defined asset allocation policy you can stick with come hell or high water. Don’t let the perfect be the enemy of the good; a “suboptimal” asset allocation you can carry out is better than an optimal one you’ll abandon when things get scary—as they will at least once every several years.

Images   A serviceable asset allocation can be as simple as a single target-date fund or as complex as one with a dozen different stock asset classes. Where you are on this complexity spectrum depends on how good you are at math and how well you tolerate a complicated portfolio. Sticking with with your chosen strategy matters far more than its precise asset allocation policy.

Images   The most difficult asset allocation operation involves deploying a large lump sum. Most of the time you’ll do better by investing it all at once, but doing so gradually with either value averaging or DCA is much easier on your psyche.

Images   When and how to rebalance your portfolio depends on how much time and effort you want to put in. Threshold rebalancing demands more quantitative skill than calendar rebalancing, which can be accomplished once every one to three years. Ideally, you should have enough tax-sheltered retirement assets to rebalance all of your portfolio’s stock asset classes. For those with primarily taxable portfolios, the capital gains incurred by selling the best-performing stock asset classes mitigate against aggressively doing so. You rebalance your portfolio mainly to reduce risk, but also to build up and sustain the emotional fortitude needed, in Warren Buffett’s famous words, to be “fearful when others are greedy and greedy when others are fearful.”

Images   When and how to reduce your equity exposure as retirement approaches depends primarily on your burn rate. The higher the burn rate, the more aggressively you should cut back a high equity exposure as you approach retirement.

* The classic three-fund portfolio uses the Total Bond Index Fund, but because of Ted’s fear of inflation, he’s chosen the shorter maturity bond index fund. For a fuller description of the Boglehead three-fund portfolio, see https://www.bogleheads.org/wiki/Three-fund_portfolio.

* It’s a lot easier to demonstrate short-term momentum than longer-period mean reversion because the far larger number of short periods provides more statistical “fuel” for analysis than the longer periods required for the analysis of mean reversion. For example, the 95 years between 1926 and 2020 supply 1,140 monthly returns, but only 19 independent 5-year periods. For a good summary of the mean reversion phenomenon, see Ronald Balvers, et al., “Mean Reversion across National Stock Markets and Parametric Contrarian Investment Strategies,” The Journal of Finance 55:2 (April 2000): 745–772.

CHAPTER 18

NUTS AND BOLTS

When I wrote this book’s first edition two decades ago, my mutual fund recommendations were stone simple: set up an account at Vanguard and buy their index funds. The only other fund family I seriously considered, Dimensional Fund Advisors (DFA), filled the deep-value corners of the market better than did the behemoth of Valley Forge, but DFA required the often-expensive services of an affiliated advisor. If you wanted free exposure to DFA’s funds, you had to be one of the lucky few with access to them in your employer’s defined-contribution (DC) plan.

Times have changed for the better. DFA’s products are now available to the general public as exchange-traded funds (ETFs), and they have plenty of competition in the factor tilt (small and value) department.

But no area has benefited more from the “Bogle revolution” than defined- contribution plans.

MOST IMPROVED PLAYER AWARD: THE 401(K)

Over the past several decades, companies have gradually closed their traditional defined-benefit plans, which provided pensions to their retired workers, and replaced them with defined-contribution schemes, most commonly 401(k)s.

This shift in retirement funding offloaded the risk of shortfall (in plain English, living over your kid’s garage) from employers to employees—good for them, bad for you. Saving and investing for retirement and then spending it down require no small amount of ability, investment knowledge, and self-discipline, and it strains credulity to expect the average worker to execute all these things well. Imagine boarding an airliner. Instead of turning right and heading to your seat, the flight attendant tells you that the pilots have decided, because of the risk and stress of piloting, to stay home. Turn left at the door, please. You’re flying the plane.

Employers also adore defined-contribution plans because they are inexpensive to fund and administer. Until recently, they effectively shielded employers from liability, and employers paid scant attention to fund expenses. Before 2005 or so, the typical plan had overt costs of at least 2% per year, before adding in the plans’ hidden administrative fees.

During the 1990s, most of the stock funds offered to employees were heavily weighted with the large-cap glamour companies of that period. Many, if not most, participants selected the highest-returning funds on the plan’s list, which were most often high-octane tech funds. Things did not turn out well for those who did. At the bottom of this sorry pile of defined-contribution plans lay teachers’ 403(b) and government employees’ 457 accounts, larded with funds featuring eye-watering fees, often from insurance companies.

Over the past few decades, the average defined-contribution plan has improved. As word of the indexing advantage spread among the general public, employees and employers noticed. Most plans now offer a decent array of low-cost passive vehicles. The work of behavioral economists such as Richard Thaler has made inexpensive, easy-to-deploy target-date funds the default choice in many schemes, and research firms such as BrightScope have applied sunlight disinfectant to exploitative and Byzantine defined-contribution fee structures.

The courts also made a significant contribution. A tort attorney named Jerome Schlichter did well by doing good—and continues to do so—with dozens of high-profile cases against large companies that failed to uphold their fiduciary responsibilities to their employee plan participants. In the bad old days, in Schlichter’s words, “Nobody’s bonus depended on how the 401(k) plan was managed.” Few attorneys have the honor of having a past participle named after them, in this case “Schlichterized,” a fearsome prospect for any corporate legal department.¹

Thanks to John Bogle, Richard Thaler, BrightScope, and Jerome Schlichter, your 401(k) plan should feature a decent selection of low-cost index and target-date funds. But there are still a lot of old plans packed with miserable, high-cost actively managed mutual funds. If you see insurance company names in the list, your HR director may be enjoying the plan administrator’s skybox seats. In that case, you and your coworkers may or may not protest successfully. If not, take maximum advantage of the employer match and invest, to the extent your income and living expenses allow, any savings beyond that in a personal IRA at a low-cost provider. The moment you terminate your employment, roll the assets over into a personal IRA.

YOUR PERSONAL ACCOUNTS

At large companies, you usually don’t have a lot to say about your defined-contribution plan’s fund choices. On the other hand, you have free choice about where to house your IRAs and taxable assets. Until recently, John Bogle’s Vanguard Group stood head and shoulders above everyone else in terms of delivering the best funds at the lowest cost.

No longer. What Bloomberg analyst Eric Balchunas has labeled “The Vanguard Effect”—the existential threat it posed to other large investment companies such as Fidelity, Schwab, and the old wire houses—has forced the rest of the industry to compete with Vanguard on price.

And oh my, are they competing. Not only do the likes of Schwab and Fidelity have a lineup of their own dirt-cheap, open-end index funds (some of Fidelity’s have a zero expense ratio), but investors can now assemble a portfolio of rock-bottom-cost ETFs at many brokerage houses, including Vanguard’s, free of commissions and fees.

The quality gap between the Vanguard Group and the rest of the investing industry is largely gone. As an admirer of the late John Bogle, it pains me to admit that customer support at Vanguard has deteriorated, with not infrequent clerical errors and extended phone hold times, in contrast to the generally fast, knowledgeable, and accurate support at other firms. How long this free ride for small investors at companies like Fidelity and Schwab lasts is anyone’s guess, so enjoy it while it does.

TO ETF OR NOT TO ETF

In 1993, State Street Global Advisors listed the first ETF. Its ticker was SPY, but it was better known as SPDR (Standard & Poor’s Depository Receipts). A decade later, there were 276 ETFs. As of 2021, that number had grown to 8,552 and counting. Until 2008, all ETFs were passively managed; today, 98% still are.

Today’s small investor is faced with major-league choice paralysis, since multiple providers offer ETFs in every conceivable asset class. (Defined-contribution plan participants are largely protected from the choice paralysis problem, since most large and midsize company plans limit investment fund picks to a relatively few, plain-vanilla, open-end vehicles and do not offer ETFs.)

For the most encompassing asset classes, such as the US total stock market, S&P 500, or MSCI EAFE index of foreign developed stocks, the ETFs and open-end mutual funds from the major providers have low expense ratios, and in most cases, they provide nearly identical returns. You should, though, pay attention to the number of securities held by any fund, open-end or ETF. As of this book’s writing, the Schwab International (open-end) Index Fund owns only 855 names, versus 1,527 for its ETF version. Vanguard’s offerings own 7,881 names. Even this large difference has little effect on long-term returns, since the missing names in the Schwab funds are of firms with small market capitalizations.

Here are the rules of the road for housing your personal accounts at the Big Three: Vanguard, Schwab, and Fidelity:

Images   Limit your purchases of open-end funds to those of your custodian. For example, if you house your assets at Fidelity, use only Fidelity’s open-end index funds.

Images   ETFs from any company can be traded online without commission at all three brokerages. Trades made through a live broker will likely incur a commission. Always place ETF trades as a limit order, and avoid buying and selling during the first and last 30 minutes of the trading day, when pricing and spreads can be erratic. Pay special attention to the price spreads, which I’ve listed in this chapter’s tables, particularly for smaller funds. Current spread data is easily available from many firms’ websites. Fidelity’s is especially easy to navigate.

Images   Treasuries can be purchased at auction and bought and sold in the secondary market (after auction but before maturity) commission-free at all three companies. If you plan to trade Treasuries in the secondary market, I’d still confirm commission details with the brokerage. This is especially important at Schwab, whose sweep vehicle money market yields are well below market levels.

Images   Fidelity and Schwab offer online banking, but Vanguard does not. Vanguard also charges a $20 annual fee below certain asset levels, which can be avoided by electronic-only document delivery.

Why do Fidelity and Schwab offer a free ride to someone who assembles a portfolio of another company’s ETFs? They’re not talking. It seems likely that Fidelity wants to tempt you with their actively managed funds. At Schwab, the answer is more clear-cut. At the time of this writing, the default sweep vehicle yields 0.40%, which was 3.7% lower than the concurrent yield of Vanguard’s Treasury Money Market Fund. Financial author and advisor Allan Roth calculated that in 2019, 134% of the Schwab’s earnings came from net interest, that is, paying customers a pitiful yield on their account balances and loaning out those balances at far higher rates.² (The 134% earnings figure means that the rest of the company’s operations lost money, including the brokerage free ride.)

Don’t fall for those games at either Fidelity or Schwab. Stay away from Fidelity’s actively managed funds. Triple-check a fund’s expenses before buying, and be especially cognizant of the difference between its target date “Freedom” funds, which have high expenses, and its “Freedom Index” funds, whose expenses are competitive with Vanguard’s. At Schwab, keep your cash balances at a minimum with the purchase of a T-bill ladder, a short-term Treasury ETF, or one of their separate money market funds (whose purchase and sale require separate transactions). The iShares 0–3 Month Treasury Bond ETF (SGOV), for example, with a duration of 0.1 years, approximates a Treasury money market fund, the main difference being that its net asset value (NAV) will vary, as opposed to the constant $1.00 of a conventional money market fund.

Some brokerages pay for free trading with payments for order flow (PFOF). This mechanism involves rebates from the wholesale brokers who execute the trades, who make a profit from the bid/ask spread on the stock or ETF. Currently, Schwab does accept PFOF; Fidelity and Vanguard do not.³ Vanguard’s higher money market interest and superb ETF executions are a plus; its poor service and lack of online banking are minuses. I’d still give a slight nod to Vanguard ETFs and open-end funds because of the company’s investment culture, which flows from a nonprofit structure that returns savings to its funds’ shareholders. Schwab, State Street, and BlackRock, on the other hand, are publicly traded companies and suffer from very real conflicts of interest between the companies’ shareholders and their funds’ shareholders. Fidelity is owned by the Johnson family; privately held companies’ ethical behavior generally lies midway between those of mutualized and publicly traded firms.

For example, Vanguard returns 100% of the profits from share lending to their funds’ shareholders, while Fidelity, Schwab, and BlackRock/iShares don’t. (These profits are tiny for large-cap funds but are more important for small-cap funds.) Finally, because of its opaque compensation structure, even Vanguard is not entirely above suspicion.

Competition among the major custodians will only intensify, so stay tuned, as their relative advantages and disadvantages can easily change.

THE PORTFOLIO WORKHORSE: TOTAL STOCK MARKET FUNDS

All the investment companies I’ve mentioned—Fidelity, Vanguard, BlackRock, State Street, and Schwab—offer total market index funds for US equities. Each company offers these vehicles in either open-end or ETF wrappers, and often in both, as listed in Table 18.1. (A fast bit of housekeeping regarding this chapter’s fund tables: All the listed Vanguard funds are for their Admiral Class shares, which in most cases carry fund minimums of $3,000, but in some cases can run as high as $50,000. Given the enormous and ever-growing number of open-end funds and ETFs, these tables cannot hope to be comprehensive or up to date. For example, I’ve listed Dimensional’s ETFs but omitted their open-end funds, which are available only to those with affiliated advisors or to some defined contribution plan participants. Keep current on the evolving fund scene with the Morningstar fund research utility described in Chapter 15.)

Next in Table 18.1 come “one-stop shopping” world equity funds, which also include US equities. In the past, these were unattractive vehicles because of their relatively high cost and more than 50% foreign weighting. Over the last few years, both of these problems have disappeared. The domestic/foreign split of these vehicles currently stands at about 61/39, and while cost-conscious investors can still save a tiny amount by assembling the same portfolio from US and foreign equity components, many will find the convenience and diversification of owning a single world stock fund worth its small extra cost. The final fund groups in Table 18.1 are total stock market funds that cover all non-US stocks, both in developed and emerging markets.

Table 18.1 Total Stock Market Funds

Total US Stock Market Funds

Total World Stock Market Funds

Total International Funds (All ex-US Stocks)

Source data: Morningstar

The biggest difference between open-end funds and ETFs is their trading psychology. In terms of long-period returns, it matters little which of the two wrappers you choose. The choice will depend on how you deal with the psychology of open-end funds’ end-of-day pricing versus ETFs’ continuous pricing. With an open-end fund, you get the closing price of its underlying securities, while an ETF trades continuously throughout the day and you decide when to pull the trigger. Both of these situations can cause a small amount of stress, and which you prefer is a personal matter.

As you can see from the tables, these vehicles have near-zero expense ratios (and in Fidelity’s case, zero). One of these funds will suffice on the equity side for the simpler asset allocations from Chapter 7.

US LARGE-CAP FUNDS

This category, listed in Table 18.2, includes the granddaddies of indexing, Vanguard’s S&P 500 Index Fund and the SPDR S&P 500 ETF (SPY). You might want to own a US large-cap fund instead of a total market fund if you’re a “splitter” who desires a complex portfolio that separates your market exposure into large-cap and small-cap allocations.

Table 18.2 US Large-Cap Funds

Source data: Morningstar

I’ve used the terms “passive” and “index” interchangeably, but strictly speaking, they’re not the same thing. Total market funds are best described as passive, since their stock selection process mandates owning all of the publicly traded stocks in the United States or abroad in cap-weighted fashion. Large-cap vehicles are index funds, since they most often hew to a particular index. The funds in Table 18.2 variously stick to the S&P 500, Russell 1000, CRSP US Large Cap, and so on. These firms actively choose their compositions. The S&P Index Committee selects which companies to include in its indices, adding and deleting companies at the end of each year. Rebalancing the index can be a huge deal, as when Tesla joined the S&P 500 in December 2020.

A company’s addition to the S&P 500 Index means S&P 500 Index funds must purchase its shares, which boosts that company’s share price. Hedge fund managers and other arbitrageurs “front run” the index by buying up the shares of likely additions in advance, then selling them at a higher price after a company formally joins the index. This presents index fund managers with a dilemma. They can avoid being victimized by the arbitrageurs by front-running themselves. But this also increases the fund’s tracking error, the gap between the fund’s performance and that of the index.

The more popular the index, the bigger the problem. This is why, if you want to own a pure large-cap US stock fund, you can mitigate the S&P 500 Index churn problem by using one of the funds in Table 18.2 that follows a less popular index than the S&P 500.

All the index and fund providers use slightly different stock selection criteria. For example, the S&P 500 does not hold the 500 largest US companies, but rather the “leaders” in their fields, as determined by the S&P committee. A few of its stocks are relatively small. Russell’s criteria, on the other hand, are more quantitative. Its “total market” index, the Russell 3000, includes the 3,000 largest companies by market cap, which make up 97% of total US market cap. Does that make the Russell 3000 EFT passive or indexed? Since the composition of that “index” so closely matches that of the total stock market, it hardly matters. (To complicate matters even more, the Vanguard Russell 3000 ETF contains 3,001 names, whereas the iShares offering currently contains 2,571 and is 0.10% more expensive to boot. You’re likely slightly better off owning a total stock market fund with a lower expense.)

Thousands of domestic, global, and international indices now confront investors. The different index and fund providers, with their changing market cap and equity characteristics, deploy different rules about exactly when and how companies move from one index to another.

For an individual investor, the various index construction mechanisms matter little. Rather than focus on an index provider’s precise selection criteria, pay attention to a fund’s aggregate characteristics, the most important of which are its average market cap and where its holdings lie on the value/growth dimension, as reflected in its ratios of price to book value, earnings, cash flow, sales, and dividends. These parameters are available from multiple sources, including the Morningstar fund pages.

Table 18.3 breaks the international stock market fund bucket into the stocks of wealthy, developed nations and emerging market nations, then breaks the developed group into European and Pacific regions. If you split your foreign holdings into European, Pacific, and emerging market funds, none of those three will own Canadian stocks, which are included in the world, total international, and many developed market funds, and which constitute about 3% of the total world market cap. They are heavily weighted to natural resource companies. (The widely used MSCI-EAFE index of developed markets also does not contain Canadian stocks.)

Table 18.3 International/Regional Large-Cap/Total Market Funds

Developed Markets Funds

European Stocks

Pacific Stocks

Emerging Markets Stocks

Source data: Morningstar

Different funds use different indices, so if you do split your foreign holdings up this way, use the funds from just one company. Don’t mix and match. Vanguard’s FTSE-based index funds, for example, put South Korea into the developed markets basket, while iShares’ MSCI-based ones puts it into an emerging markets basket.

TO TILT OR NOT TO TILT

Chapter 2 discussed whether it was possible to improve returns by “tilting” the portfolio toward various risk factors, the oldest of which were toward small stocks and value stocks, with the strongest evidence in favor of the latter. Other “tilts” toward stocks with higher profitability and lower capital investment may or may not increase returns. Another returns factor is price momentum. For example, stocks with high relative returns in the past 6 to 12 months have higher relative returns in the next period as well. More likely than not, though, the high turnover cost of momentum strategies wipes out their excess returns.

Tilting toward large value and small value stocks can get complicated, since some of the products from smaller companies, such as Invesco, Avantis, and Dimensional, have higher tilts and slightly higher fund fees and spreads, and vary widely in design, composition, and performance. Over time, the long-term returns of different small value funds should converge, but from year to year the performance variation can be striking. In particular, over the past decade the value factor has performed relatively poorly, as reflected in the fund performance. For this reason, I’ve intentionally left out fund performances from the tables later in this chapter.

If you do tilt, be aware that different fund companies tilt toward different factors. All tilt toward value, but to differing degrees and according to the metrics they use to define “value,” such as low multiples of book value, earnings, dividends, cash flow, and so forth, and, as displayed in Table 18.4, to profitability and to capital investment as well. Note the differences among tilted funds, as well as their industry exposures, which can be found on Morningstar’s site. For example, the REIT composition of the small value funds in Table 18.4 runs at around 10%. In contrast, the Avantis and Dimensional funds hold almost no REITs.

Table 18.4 US Small Value Stock Funds

US Large Value Stock Funds

US Small Cap Stock Funds

Source data: Morningstar

An even more complicated method of factor exposure might be to allocate the US equities among the “four corners” of the US market: large market, large value, small market, and small value. If you also split developed and emerging market stocks into the same four subcomponents, your portfolio now has 12 equity asset classes. That’s before you include REITs, precious metals stocks, and energy stocks.

The marginal benefits of this sort of asset-class splitting obey the law of diminishing returns. Such a complicated portfolio may not be worth the effort for all but the most dedicated of asset class junkies. If you want to tilt, just add a single small value fund to your US and developed foreign total stock market exposure. A modest tilt would make the small value component roughly one-third the size of the total market component, as with the last model portfolio in Chapter 17, which allocated 30% of equities to US total stock market and 10% to US small value.

A bigger tilt toward small value stocks would assign equal weights to total market and small cap value, which would be 20% of the total stock allocation in the above portfolio each to US total stock market and US small value. Tilting toward small value in emerging markets is especially problematic, since currently only one company, WisdomTree, offers a fund in this category. In this case I’d consider a large-cap value emerging markets fund instead, for which more choices exist; of these, the Avantis Emerging Markets Value Fund has the smallest average market cap.

The most important factor in deciding whether to tilt and by how much is the amount of discipline required to see tilted portfolios through their inevitable periods of relative underperformance. The US value factor return has been negative for the better part of two decades. The high value spread between growth and value companies suggests that it will make a comeback, but there’s no guarantee. After all, the value factor is a risk factor, and the biggest risk is that its risk premium may never return. If you tilt and it turns around, you’ll feel vindicated; if it doesn’t, be prepared for a barrage of I-told-you-sos.

Table 18.4 lists US tilted funds by category, and Table 18.5 lists foreign and domestic tilted funds. Both tables start with the small value category. They demonstrate another cost of tilting: their higher fund fees and ETF spreads.

Table 18.5 International Tilted Stock Funds

International Small Value Stock Funds

International Large Value Stock Funds

International Small Cap Stock Funds

Emgerging Markets Value

Emerging Markets Small/Small Value

Source data: Morningstar

Before the widespread ETF availability, open-end funds tended to distribute relatively large amounts of capital gains as stocks “grew out of” their categories and had to be sold, particularly in asset classes tilted toward small and value stocks. Consequently, it was advisable to hold tilted assets in tax-sheltered retirement accounts wherever possible.

The ETF “solved” this problem with its “in-kind” redemption process, which lets the fund distribute the most highly appreciated shares without having to sell them and capture capital gains. Investors can currently hold even tilted ETFs in a taxable portfolio without worrying about significant capital gains distributions. I put the word “solved” in quotes above for a reason: the IRS and some legislators have their eyes on this loophole, and its survival is by no means assured.

Table 18.6 Specialty Funds

US REIT Index Funds

Global REIT Funds

International REIT Funds

Precious Metals Equity Funds

Energy Stock Funds

Source data: Morningstar

WHAT ABOUT BONDS?

Your stock assets should take risks and consequently offer high expected (but not always realized) returns. Your bonds should maintain your equanimity and let you sleep. Both corporations and state and local governments can default, and few financial surprises are more alarming than finding out that assets you thought were safe aren’t. Most of your long-term investment return will be determined by how you behave in the worst 2% of the time. Deploy your fixed-income assets with that in mind.

Don’t let the tax tail wag your asset allocation dog. If you feel compelled to own municipal bonds, limit them to no more than one-third of your fixed-income assets. Do not concentrate their risk by owning only single-state vehicles. The downside potential of a default in your home state is not worth a few dozen basis points of after-tax yield.

Do not own municipal or corporate bonds in an ETF. During a severe market turbulence, these can suffer what’s called a “liquidity mismatch” between the low trading volume of many municipal and corporate bonds and the high trading volume of the ETFs that own them. This mismatch can cause wide ETF bid-ask spreads and extract real transactional costs from their motivated sellers. Even if you won’t need to tap savings for liquidity, in the worst of times the psychological pain of temporary losses just might send your portfolio skidding off the highway of riches.

I’m not wild about bond index funds either, since about a third of their holdings consist of corporate bonds and asset-backed securities, such as mortgage vehicles, that lack government guarantees. In 2008, total bond funds suffered only minor losses because the gains in their Treasury and agency holdings mitigated the damage incurred in their corporate and asset-backed bonds. Next time, things might be different.

So take as much risk as you like with equities, but center your fixed-income assets on debt with a government guarantee: CDs in amounts below the $250,000 per person FDIC limit and Treasuries. Ideally, you should purchase Treasuries at auction and sell them as needed in the secondary market. If that’s too much work, purchase a Treasury ETF or open-end Treasury mutual fund. (Treasuries are highly liquid, and it’s fine to own them in an ETF, since they’re not likely to be subject to liquidity mismatch.)

Finally, the safest way to meet retirement expenses is a TIPS ladder whose annual maturities match your need for living expenses. Theoretically you should do this is with a ladder of 30 annual rungs (or perhaps fewer, more widely spaced ones), beginning with the first year of retirement. As already mentioned, no TIPS mature between 2034, although this is a problem that will slowly disappear with successive 10-year auctions by 2029. The US Treasury only issues TIPS at maturities of 5, 10, and 30 years, which makes buying a 30-year ladder only from auctions problematic. For this reason, you’ll need to make some purchases in the secondary market. Alternatively, you can approximate a TIPS ladder with a mix of long-, intermediate-, and short-term TIPS funds, the main problem, at least at present, being the lack of a low-cost long-term vehicle. Another disadvantage of a TIPS fund is the absence of the certainty of inflation-adjusted purchasing power at maturity; if TIPS yields rise, you’ll be dealing with selling at a depressed price.

Table 18.7 lists various classes of bond mutual funds.

Table 18.7 Bond Mutual Funds

Short-Term Treasury Funds

Longer-Term Treasury Bond Funds

Treasury Inflation-Protected Securities (TIPS)

Short-Term Bond Index

Total Bond Index

National Municipal Bond Funds

*Admiral Class shares with $50,000 minimum; Investor Class funds have $3,000 minimum and 0.17% expense ratio.

Corporate Bond Funds

Source data: Morningstar

WHEN ETFS GO BAD: THEMATIC AND LEVERAGED/INVERSE FUNDS

Wall Street eventually runs every good idea into the ground. This happened quickly with ETFs, which have seen the proliferation of hot-money vehicles aimed at poorly informed and narrative-influenced investors, such as the wound care and agribusiness ETFs mentioned in Chapter 14, and more recently a slew of marijuana- and cryptocurrency-related offerings. If this book has done its job, the last sentence sent your eyes on a big, slow roll.

Leveraged and inverse funds are another class of toxic ETFs. A leveraged fund uses borrowed funds and derivatives to multiply an index’s daily return, usually by a factor of two or three. What’s called “variance drag,” or the way volatility corrodes return, makes this is a truly awful idea. (The first math box in Chapter 1 explains this phenomenon.)

ProShares Ultra Real Estate ETF (URE), which aims to produce twice the daily return of an index of REITs, is one of the oldest leveraged funds. The Vanguard Real Estate Fund ETF (VNQ) returned an annualized 6.22% for the 15-year period ending April 2022, not bad considering that the measurement period began at the end of April 2007, near the peak of the real estate bubble that gave rise to the global financial crisis. URE’s return over the same period was −1.99% per year.

Since stocks generally have a positive long-term return, shorting them is usually a losing strategy. But you can do something even worse: shorting them with leverage. Amazingly, ProShares offers the speculating public a fund that offers the opposite of twice the daily return of the Dow Jones Real Estate Index. Its Ultra Short Real Estate Fund (SRS) gave its “investors” a 15-year annualized return of –34.57%. You read that right: had you “invested” $1,000 in SRS in April 2007, by April 2022 you’d have $1.72.

Why do these funds exist? The rationale offered by their issuers defies both logic and simple arithmetic. It goes something like this: “These vehicles are not designed to be long-term holdings. You should only own them for brief periods of time to protect yourself from sudden price falls.” But if something is a lousy long-term holding, it’s a lousy short-term one as well. Consider SRS’s −34.57% annualized return, which implies a monthly return of −3.47%. If you want to hedge against a sudden fall in REITs, simply selling them down is a far better choice than losing on average 3.47% each month in SRS.

CHAPTER 18 SUMMARY

Images   Pay attention to the fund choices in your company’s retirement plan. If you’re stuck with a crummy one that’s packed with high-cost actively managed funds, lobby your employer to add low-cost index funds. Failing that, maximize the employer match, contribute additional savings beyond the match ceiling into a personal IRA, and roll the 401(k) assets into an IRA as soon as possible after you terminate your employment.

Images   Pick one or more custodians for your personal assets. Vanguard, Fidelity, and Schwab let you buy and sell low-cost ETFs and Treasuries commission-free. Each of the three has a downside: the poor customer service at Vanguard and subpar money market yields at Fidelity and Schwab, particularly at the latter. Avoid this by purchasing individual Treasuries or Treasury ETFs, open-end or ETF bond mutual funds, and separate money market funds instead of their default sweep vehicles. The custodian landscape is evolving. If the market gods are unkind to stocks and bonds, that landscape may evolve even more rapidly. The decision to use open-end funds instead of ETFs in your personal accounts is in most cases a matter of personal preference. ETFs that contain corporate or municipal securities may suffer from wide spreads during extreme market turbulence, the most critical stretch on the highway of riches.

Images   Portfolios tilted toward small and value stocks may or may not offer higher returns at the cost of higher complexity and higher fund fees. Whichever route you pick, there will be periods when you’ll regret your choice. Over the long haul, the discipline to stick with your chosen strategy is far more important than your precise asset allocation target.

CHAPTER 19

A FINAL WORD

This survey of personal investing covers a much wider range of topics than most books on the subject, and for good reason. As the principals of Long-Term Capital Management demonstrated all too well, without a working knowledge of investment psychology, history, and the business itself, even the world’s most brilliant masters of investment theory court disaster. While the study of each of these four broad areas is worthwhile in its own right, together they function like the four legs of a chair. Subtract even one of them, and your investment strategy will come to grief. Here’s a summary of what I’ve tried to impart.

PILLAR ONE: INVESTMENT THEORY

First and foremost, risk and return are joined at the hip. You shouldn’t work in an emergency room if gunshot wounds and severe car accidents upset you. In the same way, stock ownership sooner or later always serves up fearsome and unavoidable losses, and if you can’t handle them, then you should not own equities. On the other hand, if you desire safety, you must accept low returns. The stocks of boring, unglamorous companies must offer higher returns than the sexy ones, or no one would buy them. The same goes double for the shares of companies that are in trouble. The promise of high returns with low risk is a reliable marker for fraud.

You can roughly estimate the long-term return of the stock market by adding its long-term per-share earnings growth, which is probably no higher than 2% after inflation, to its dividend yield, which is currently about 1.7%, for a total of 3.7%. The long-term return of high-grade bonds is essentially the same as the dividend yield; the TIPS market suggests that they currently offer an approximately 1.5% real return. These estimates, however, are subject to a large amount of uncertainty, particularly over short periods, and will likely be obsolete by the time you’re reading this book.

Next, you should think of the market as terrifyingly smarter than even its wisest individual participants. Stock picking and market timing are expensive, risky, and ultimately futile exercises. By definition, a professional money manager’s expected return is the market return minus his expenses. It really is true: past performance is not indicative of future returns—not at all. Last decade’s champ is highly likely to become this decade’s chump. Moreover, you almost certainly cannot beat these professional participants at stock selection.

Further, only a small percent of stocks produce most of the market return. They are needles in the haystack, and if you own even a hundred different companies, you’re going to miss most of them. The safest bet is to own the whole haystack.

Finally, you can’t identify the portfolio composition that will perform best in the future, and the most prudent course likely is owning a widely diversified portfolio. Those who desire more complexity and want to earn a higher return can attempt to do so by taking the risk of owning small and value stocks.

PILLAR TWO: INVESTMENT HISTORY

Be prepared: the markets regularly drift off into la-la land, on both the upside and the downside. There will be times when new technologies promise to remake our economy and culture, and their sirens sing of getting in on the ground floor. When you hear this melody, hold on tight to your wallet. At other times the sky will seem to be falling. These are usually the best times to buy.

While history doesn’t repeat itself, or even rhyme, there are only so many plot trajectories of market history. Particularly when it comes to bubbles, it helps to realize that you’ve seen the movie before, and you know how this one ends.

PILLAR THREE: INVESTMENT PSYCHOLOGY

You are your own worst enemy. More likely than not, you are overconfident about your ability to pick stocks and money managers. Remember that the market is an 800-pound gorilla whose primary goal is to make as many investors look as foolish as possible. Even worse, you are also overconfident about your risk tolerance when the market sky turns dark. Always remember Fred Schwed’s observation that there are some things that cannot be conveyed to a virgin with abstractions, especially just how awful it feels to see your nest egg suddenly shrink. To reap compound interest’s bounty, you must not interrupt your investment strategy. A nice stack of Treasury securities and CDs gives you the fortitude to do that.

Your social instincts will corrode your wealth by seducing you into owning what everyone else owns. If you are invested in the same market sectors as your neighbors and friends, it is likely that you will reap low returns. Successful investing is a solitary activity.

Next, ignore the last 5 or 10 years of investment returns, and focus on the longer-term data. Yes, large growth stocks have had very high returns in recent years, but history suggests that they still underperform both large and small value stocks. While there are no guarantees that this will be true going forward, the odds always favor data gathered over the longest time periods.

Finally, resist the human temptation to imagine patterns where there are none. Asset class returns are essentially random, and patterns apparent in retrospect almost never repeat going forward.

PILLAR FOUR: INVESTMENT BUSINESS

Most brokers and advisors, especially those working at the legacy wire houses and at the more recent independent broker-dealers, service their clients in the same way Bonnie and Clyde serviced car deealerships. They occupy the lowest rung in the hierarchy of investment knowledge, and simply reading this book means you probably know more about investing than they do.

The mutual fund landscape, on the other hand, has become less fraught over the past few decades, but you still need to pay close attention to your fund company’s ownership structure and fees. Never forget that the primary business of most fund companies is collecting assets, not managing money.

Educate yourself, but be careful: when it comes to investing, 99% of what you see in magazines, newspapers, and social media is worse than worthless. The one exception to this is financial “news” on cable television, where that figure rises to 100%. Most financial journalists quickly learn that it is much easier to churn out a stream of froth about temporarily lucky strategists and fund managers than to do serious analysis. Happily, the internet is not a complete investment wasteland. YouTube and podcasts abound with useful content, but only if you know in advance whom to listen to. A good place to start would be the authors of the academic papers referenced in this book, particularly Eugene Fama, Kenneth French, the late Paul Samuelson, Zvi Bodie, and Robert Shiller.

***

While you might be able to manage your finances with just the information between these covers, you’d be foolish to do so. This book is a framework to which you’ll continuously add knowledge, starting with the sources I’ve mentioned.

The overarching message of this book is at once powerful and simple: with relatively little effort, you can design and assemble an investment portfolio with wide diversification and minimal expense, and it will prove superior to most professionally managed accounts. You don’t need great intelligence and good luck. The essential characteristics of the successful investor are the discipline and the stamina to “stay the course,” as Jack Bogle famously said.

Your financial security rests on four pillars: your knowledge of the theory, history, psychology, and business of investing. Learn them well and use them wisely.

NOTES

INTRODUCTION

1.   Roger Lowenstein, When Genius Failed (New York: Random House, 2000).

2.   Corey Kligannon, “96-year-old secretary quietly amasses fortune, then donates $8.2 million,” The New York Times, May 6, 2018; Paul Hyams and Jane Lockshin, personal communication.

3.   Warren Buffett, speech at University of Florida School of Business, October 1998, https://m.youtube.com/watch?v=2MHIcabnjrA; the section on LTCM begins at 13:00, the quote begins at 17:30.

4.   For “Half of everything is geography; the other half is Shakespeare,” see https://spectatorworld.com/book-and-art/travels-robert-d-kaplan-good-american-robert-gersony/.

5.   Vanguard Total Stock Market Index Fund, Admiral class shares, as of October 9, 2007, March 9, 2009, and December 31, 2022.

6.   John Maynard Keynes and Donald Moggridge, eds., The Collected Writings of John Maynard Keynes, Volume XII, Economic Articles and Correspondence: Investment and Editorial (London: Macmillan for the Royal Economic Society, 1983), 38.

CHAPTER 1

1.   James K. Glassman and Kevin A. Hassett, Dow 36,000 (New York: Crown Business, 1999).

2.   Elroy Dimson, et al., Triumph of the Optimists (Princeton: Princeton University Press, 2002). The annual summaries are difficult to find on Credit Suisse’s website, but are easy to locate by entering the following terms into a search engine, for example, for the 2013 report: Credit Suisse, Dimson, annual report, 2013.

3.   Zvi Bodie, “On the Risk of Stocks in the Long Run,” Financial Analysts Journal 51:3 (May–June 1995): 18–22.

4.   Kay Giesecke, et al., “Corporate Bond Default Risk: A 150-Year Perspective,” Journal of Financial Economics 102:2 (November, 2011): 233–250.

5.   I’m indebted to Antti Ilmanen’s discussion in Expected Returns (Hoboken, NJ: John Wiley & Sons, 2011), 11–12, of the importance of loss timing.

6.   Calculated from Elroy Dimson, et al., Credit Suisse Global Investment Returns Yearbook 2022, 21, 25, 60.

7.   For a more detailed description of how contango corrodes commodities futures returns, see “On Stuff,” http://www.efficientfrontier.com/ef/0adhoc/stuff.htm, and also Wenjin Kang, et al., “Financialization of Commodity Markets Ten Years Later,” https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4313728, accessed January 2, 2023.

CHAPTER 2

1.   Russell J. Fuller, et al., “Returns to E/P Strategies, Higgledy-Piggledy Growth, Analysts’ Forecast Errors, and Omitted Risk Factors,” The Journal of Portfolio Management 19:2 (Winter 1993): 13–24.

2.   David N. Dreman and Michael A. Berry, “Overreaction, Underreaction, and the Low P/E Effect,” Financial Analysts Journal 51:4 (July/August 1995): 21–30.

3.   Rolf Banz, “The Relationship Between Return and Market Value of Common Stocks,” Journal of Financial Economics 9:1 (March 1981): 3–18; Eugene F. Fama and Kenneth R. French, “Size and Book-to-Market Factors in Earnings and Returns,” The Journal of Finance, 50:1 (March 1995): 131–155.

4.   For a description of the mechanism of momentum crashes, see Kent Daniel and Tobias J. Moskowitz, Journal of Financial Economics 122 (2016): 221–247.

5.   David Leinweber, “Stupid Data Miner Tricks,” annotated slide excerpts, First Quadrant Corporation.

6.   Campbell R. Harvey and Yan Liu, “A Census of the Factor Zoo,” SSRN Working Paper, February 25, 2019. The term “factor zoo” was coined by John H. Cochrane; see “Presidential Address: Discount Rates,” The Journal of Finance 66:4 (August 2011): 1047–1108.

CHAPTER 3

1.   With apologies to Burton Malkiel, A Random Walk Down Wall Street (New York: W.W. Norton & Company, 2007), 17, 24.

2.   James Owen Weatherall, The Physics of Wall Street (Boston: Houghton Mifflin Harcourt, 2013), 1–2; Louis Bachelier, Louis Bachelier’s Theory of Speculation, Mark Davis and Alison Etherige, trans. (Princeton, NJ: Princeton University Press, 2006), 33.

3.   Jeremy Bernstein, “Paul Samuelson and the Obscure Origins of the Financial Crisis,” New York Review of Books, January 11, 2010; John C. Bogle, “The Professor, the Student, and the Index Fund,” http://johncbogle.com/wordpress/wp-content/uploads/2011/09/The-Professor-The-Student-and-the-Index-Fund-9-4-11.pdf, accessed December 21, 2021; Paul Samuelson, “Challenge to Judgment,” The Journal of Portfolio Management 1:1 (Fall 1974): 17–19.

4.   The quote, which came from an address to the Purchasing Agents Association at the Builders Exchange Club in New York, was printed in The New York Times on October 16, 1929, just one week before Wall Street’s Black Days began; see https://www.federalreservehistory.org/essays/stock-market-crash-of-1929.

5.   Peter L. Bernstein, Capital Ideas (New York: Free Press, 1993), 31–38.

6.   Alfred Cowles 3rd, “Can Stock Market Forecasters Forecast?” Econometrica 3:1 (July 1933): 309–324; Cowles, “Stock Market Forecasting,” Econometrica 12:3/4 (July–October 1944): 206–214.

7.   Peter L. Bernstein, Capital Ideas (New York: Free Press, 1993), 126–127.

8.   Berkshire-Hathaway 1990 annual report, http://www.berkshirehathaway.com/letters/1990.html.

9.   William F. Sharpe, “Mutual Fund Performance,” The Journal of Business 39:1, Part 2 Supplement (January 1966): 119–138 (quote 138). See also Jack Treynor, “How to Rate Performance of Investment Funds,” Harvard Business Review 43:1 (January-February 1965): 63–75.

10.   Michael C. Jensen, “The Performance of Mutual Funds in the Period 1945–1964,” The Journal of Finance 23:2 (May 1968): 389–416.

11.   https://web.stanford.edu/~wfsharpe/art/active/active.htm.

12.   The most widely quoted academic articles on the nonpersistence of mutual fund performance are Mark Carhart, “On Persistence in Mutual Fund Performance,” The Journal of Finance 52:1 (March 1997): 57–82; Jonathan B. Berk and Richard C. Green, “Mutual Fund Flows and Performance in Rational Markets,” The Journal of Political Economy 112:6 (December 2004): 1269–1295; and Shawn Phelps and Larry Detzel, “The Nonpersistence of Mutual Fund Performance,” Quarterly Journal of Business and Economics 36:2 (Spring 1997): 55–69.

13.   Edwin J. Elton, et al., “Survivorship Bias and Mutual Fund Performance,” The Review of Financial Studies 9:4 (Winter 1996): 1097–1120; Martin Rohleder, et al., “Survivorship Bias and Mutual Fund Performance: Relevance, Significance, and Methodical Differences,” working paper, 2011.

14.   Francis Galton, “Vox Populi,” Nature, 75:1949 (March 7, 1907): 450–451; Galton, Letters to the Editor, Nature 75:1952 (March 28, 1907): 509–510.

15.   Sherry Sontag and Christopher Drew, Blind Man’s Bluff (New York: HarperPaperbacks, 1999), 63–65, 96–117.

16.   For financial pornography, see Jane Bryant Quinn, “When Business Writing Becomes Soft Porn (How Journalists Cover Personal Finance),” Columbia Journalism Review, 36:6 (March 1, 1998): 48.

17.   Amy Arnott, “ARKK: An Object Lesson in How Not to Invest,” https://www.morningstar.com/articles/1071658/arkk-an-object-lesson-in-how-not-to-invest, December 13, 2021; and Amy Arnott, personal communication. Returns for 11/1/14 to 11/30/21, and Harriet Agnew, “Ark Invest CEO Cathie Wood on Everything from Deflation to Elon Musk,” FT Magazine, March 2, 2022.

18.   Robby Greengold, “ARK Innovation ETF’s Approach Is Ill-Timed for a Major Twist,” https://www.morningstar.com/articles/1031702/ark-innovation-etfs-approach-is-ill-timed-for-a-major-twist, accessed December 31, 2021.

19.   George Santayana, The Life of Reason, Volume VII, Book One (Cambridge MA: MIT Press, 2011), 172.

20.   John Brooks, The Go-Go Years (Hoboken, NJ: John Wiley & Sons, 1999): 134.

21.   Brooks, 130–149; also see Federal Register Notices 35:111 (June 9, 1970): 8901.

22.   Tom Lauricella, “The Stock Picker’s Defeat,” The Wall Street Journal (December 10, 2008), C1.

23.   Jonathan Clements, “Excuses, Excuses,” The Wall Street Journal, April 10, 2001.

24.   Christopher Drew, “Joseph E. Granville, Stock Market Predictor, Dies at 90,” The New York Times, September 19, 2003. Granville was also the author of the newsletter cited by Graham and Harvey with the −4.9% 12½-year loss.

25.   Ibid.

26.   Floyd Norris, “Garzarelli Is Ousted by Lehman, The New York Times, October 27, 1994; “Garzarelli to Liquidate Her 6-Month-Old Fund, Los Angeles Times, November 6, 1997; quote from David Rynecki, “Timing Matters,” Fortune, October 13, 2003.

27.   Ali Hussain, “I’m 95% in Cash, Says Dr. Doom; Fame & Fortune, Nouriel Roubini Talks to Ali Hussain,” Times (London), June 21, 2009.

28.   John R. Graham and Campbell R. Harvey, “Grading the Performance of Market-Timing Newsletters,” Financial Analysts Journal 53: 6 (November–December, 1997): 54–66. The working paper version of this article, which contains a table listing the performance of individual newsletters, including the one referenced, can be found at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6006.

29.   Andrew Metrick, “Performance Evaluation with Transactions Data: The Stock Selection of Investment Newsletters,” NBER Working Paper 6648, July 1998.

30.   Hendrick Bessembinder, “Do Stocks Outperform Treasury Bills?” The Journal of Financial Economics 129 (2018): 440–457.

31.   Christopher J. Chipella, et al., “Both Fidelity Investors and Firm Are at Sea as Magellan Boss Goes,” The Wall Street Journal, March 29, 1990; Jonathan Clements, “Can Lynch Live up to His Reputation?” Forbes, April 3, 1989; Joseph Nocera, A Piece of the Action (New York: Simon & Schuster, 1994), 239–249.

32.   Jason Zweig, “What You Can Learn from One of Warren Buffett’s Smartest Investors,” The Wall Street Journal, December 21, 2018.

33.   Kenneth French online data library, https://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html.

34.   Jason Zweig, “Meet the Kidd Who Goes Toe to Toe with Warren Buffett,” The Wall Street Journal, December 10, 2021.

35.   Gregory Zuckerman, The Man Who Solved the Market (New York: Penguin, 2019), 247, 315–319.

CHAPTER 4

1.   Eric Zimmerman, “Burr Told Family to Withdraw Everything from Bank,” The Hill, April 4, 2009.

2.   See, for example, Benoit Mandelbrot, “The Variation of Certain Speculative Prices,” The Journal of Business 36:4 (October 1963): 394–419; Eugene Fama, “The Behavior of Stock Market Prices,” The Journal of Business 38:1 (January 1965): 34–105.

3.   Regarding power-law relationships of terrorist attacks, earthquakes, and meteoroid strikes, see Nate Silver, The Signal and the Noise (New York: The Penguin Press, 2012), 149–172, 428–432; P. G. Brown, et al., “A 500-kiloton Airburst over Chelyabinsk and an Enhanced Hazard from Small Impactors,” Nature, 503 (November 14, 2013): 238–241.

4.   See, for example, http://www.efficientfrontier.com/ef/104/iid.htm, and Xavier Gabaix, et al., “Power Laws in Economics and Finance,” Annual Review of Economics 1 (2009): 255–293.

5.   Bernstein, The Intelligent Asset Allocator, 132–137, and Wen Dai and Warwick Schneller, “To Hedge or Not to Hedge: A Framework for Currency Hedging Decisions in Global Equity & Fixed Income Portfolios,” https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3703333.

6.   John C. Bogle, John C. Bogle on Investing (Hoboken, NJ: John Wiley & Sons), 62.

CHAPTER 5

1.   Harry Markowitz, “Portfolio Selection,” The Journal of Finance 7:1 (March 1952), 77–91.

2.   Jason Zweig, “Investing Lessons from America’s Top Pension Fund,” Money, January 1998.

3.   Philologos, “The Rest of ‘The Rest Is Commentary’,” The Jewish Daily Forward, September 24, 2008, http://forward.com/articles/14250/the-rest-of-the-rest-is-commentary-/.

CHAPTER 6

1.   Paul A. Samuelson, “Lifetime Portfolio Selection by Dynamic Stochastic Programming,” The Review of Economics and Statistics 51:3 (August 1969): 237–46; Robert C. Merton, “Lifetime Portfolio Selection Under Uncertainty: The Continuous-time Case,” The Review of Economics and Statistics 51:3 (August 1969): 247–57; Zvi Bodie, et al., “Labor Supply Flexibility and Portfolio Choice in a Life-Cycle Model,” NBER Working Paper Series No. 3954, January 1992.

2.   Ian Ayres and Barry J. Nalebuff, “Life-cycle Investing and Leverage: Buying Stock on Margin Can Reduce Retirement Risk,” NBER Working Paper Series No. 14094, June 2008; Ayres and Nalebuff, Lifecycle Investing (New York: Basic Books, 2010).

3.   Fred Schwed, Where Are the Customers’ Yachts? (Hoboken, NJ: John Wiley & Sons, 2006), 54.

4.   See http://www.youtube.com/watch?v=0h9tKy3NA-U%5d, at about the 16-minute mark.

5.   Robert B. Barsky, et al., “Preference Parameters and Behavioral Heterogeneity: An Experimental Approach in the Health and Retirement Study,” The Quarterly Journal of Economics 112:2 (May 1997): 540.

6.   Ibid., 537–539.

7.   William J. Bernstein, The Ages of the Investor (Efficient Frontier Publications, 2012).

8.   Philip L. Cooley, et al., “Retirement Savings: Choosing a Withdrawal Rate That Is Sustainable,” AAII Journal 10:3 (February 1998): 16–21; William P. Bengen, “Determining Withdrawal Rates Using Historical Data,” The Journal of Financial Planning 7:4 (October 1994): 171–180.

9.   Possibly apocryphal quote; see Emma Span, 90% of the Game Is Half Mental (New York: Random House, 2010), xii.

10.   Wade D. Pfau and Michael E. Kitces, “Reducing Retirement Risk with a Rising Equity Glide Path,” The Journal of Financial Planning 27:1 (January 2014): 38–48.

11.   Michael Zwecher, Retirement Portfolios (Hoboken NJ: John Wiley & Sons, 2010).

CHAPTER 8

1.   Poughkeepsie Journal, “Learn from Mistakes by Others,” April 11, 1983.

2.   Steven J. Garfinkle, “Private Enterprise in Babylonia at the End of the Third Millennium BC,” doctoral dissertation, Columbia University 2000.

3.   Sidney Homer and Richard Sylla, A History of Interest Rates, Fourth Edition (Hoboken, NJ: John Wiley & Sons, 2005), 40, 53–56, 80–83.

4.   Ibid., 21–22.

5.   Reinhold C. Mueller, The Venetian Money Market (Baltimore: Johns Hopkins University Press, 1997), 453–487.

6.   J. H. Munro, “Rentes and the European ‘Financial Revolution,’” in Gerardo Caprio, ed., Handbook of Key Global Financial Markets, Institutions, and Infrastructure (Boston: Elesvier, 2013), 241; Homer and Sylla, History of Interest Rates, 93, 99, 107.

7.   John Julius Norwich, A History of Venice (New York: Alfred A. Knopf, 1982), 243–256.

8.   Paul Ferdinand Schmelzing, “Essays on Long-Term Real Rate and Safe Asset Trends, 1311–2018,” doctoral dissertation, Harvard University, August 2019.

9.   Ibid., 87.

10.   Josh Barro, “Bernanke Says Global Imbalances Bedevil the World Economy,” The New York Times, April 2, 2015.

11.   Irving Fisher, The Theory of Interest (Philadelphia: Porcupine Press, 1977), 61–97.

12.   Geoffrey Poitras and Manuela Geranio, “Trading of Shares in the Societates Publicanorum?” Explorations in Economic History 61 (2016): 95–118.

13.   David le Bris, et al., “The Present Value Relation over Six Centuries: The Case of the Bazacle Company,” Journal of Financial Economics 132 (2019): 248–265.

14.   Ad van der Woude and Jan de Vries, The First Modern Economy (Cambridge: Cambridge University Press, 1997), 142, 145, 147, 151.

15.   Global Financial Data, https://globalfinancialdata.com/data-for-amsterdam-stocks-from-the-1600s-and-1700s-added-to-gfd.

16.   Larry Neal, The Rise of Financial Capitalism (Cambridge, UK: Cambridge University Press, 1990), 232–257.

CHAPTER 9

1.   Merle Miller, Plain Speaking (New York: Berkley Publishing Corporation, 1974), 147.

2.   Bernard Mannes Baruch, My Own Story (Ann Arbor: University of Michigan Press, 1957), 242–244; for a critical appraisal of how well Baruch avoided the Crash of 1929, see James Grant, Bernard Baruch (Hoboken, NJ: John Wiley & Sons, Inc., 1997), 209–239.

3.   Ann Goldgar, Tulipmania (Chicago: University of Chicago Press, 2007), 5–6.

4.   Edward Chancellor, Devil Take the Hindmost (New York: Penguin Group, 2000), 36–38.

5.   Charles P. Kindleberger, Manias, Panics, and Crashes (New York: John Wiley & Sons, Inc., 2000), 121, 223–232.

6.   During the late medieval period, bills of exchange also expanded credit. For a lucid description of how the modern system works, see Frederick Lewis Allen, The Lords of Creation (Chicago: Quadrangle Paperbacks, 1966), 305–306; Antoin Murphy, John Law (Oxford: Clarendon Press, 1997), 14–16.

7.   William J. Bernstein, The Birth of Plenty (New York: McGraw-Hill, 2004), 101–106.

8.   de Vries and van der Woude, The First Modern Economy.

9.   Chancellor, Devil Take the Hindmost, 30–95; and William J. Bernstein, The Delusions of Crowds (New York: Atlantic Monthly Press, 2021), 71–98. For the continent-wide mania, see Stefano Condorelli, “The 1719 Stock Euphoria: A Pan-European Perspective,” working paper, 2016, https://mpra.ub.uni-muenchen.de/68652/, accessed April 27, 2016.

10.   Chancellor, Devil Take the Hindmost, 72.

11.   Helen Paul, The South Sea Bubble (Abingdon, UK: Routledge, 2011), 1, 39–42, 59–65; John Carswell, The South Sea Bubble (Gloucestershire, UK: Sutton Publishing, Ltd., 2001), 19, 55–57, 240; Paul Harrison, “Rational Equity Valuation at the Time of the South Sea Bubble,” History of Political Economy 33:2 (Summer 2001): 269–281.

12.   Andrew Odlyzko, “Newton’s Financial Misadventures in the South Sea Bubble,” Notes and Records of the Royal Society Journal of the History of Science 73:1 (March 20, 2019): 29–59.

13.   John Francis, A History of the English Railway (London: Longman, Brown, Green, & Longmans, 1851), I:4–5.

14.   Paul Johnson, The Birth of the Modern (New York: HarperCollins Publishers, 1991), 191.

15.   Walter Bagehot, Lombard Street (New York: Scribner, Armstrong & Co., 1873), 138.

16.   Bernstein, The Delusions of Crowds, 99–121; Chancellor, Devil Take the Hindmost, 151–122, quote, 140. For the definitive contemporary description of the episode, see Francis, History of the English Railway.

17.   John K. Galbraith, The Great Crash (New York: Houghton Mifflin, 1988), 1–42.

18.   Hyman Minsky, Stabilizing an Unstable Economy (New Haven, CT: Yale University Press, 1986), 197–220.

19.   Robert Boyd and Peter J. Richerson, “Culture and the Evolution of Human Cooperation,” Philosophical Transactions of the Royal Society, 364:1533 (November 12, 2009): 3281–3288.

20.   Melanie C. Green and Timothy C. Brock, “The Role of Transportation in the Persuasiveness of Public Narratives,” Journal of Personality and Social Psychology 79:5 (2000): 701–721.

21.   David Kestenbaum, “What’s a Bubble?” http://www.npr.org/sections/money/2013/11/15/245251539/whats-a-bubble, accessed August 1, 2016.

22.   William N. Goetzmann, “Bubble Investing: Learning from History,” NBER Working Paper No. 21693, October 2015.

23.   https://www.law.cornell.edu/supremecourt/text/378/184, accessed August 1, 2016.

24.   Charles Mackay, Memoirs of Extraordinary Popular Delusions (London: Office of the National Illustrated Library, 1852), I:84.55. Andrew Odlyzko, “Charles Mackay’s Own Extraordinary Delusions and the Railway Mania,” https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1927396.

25.   William Harrison Ainsworth, The South Sea Bubble (Leipzig: Bernhard Tauchnitz, 1868), 48–49.

26.   Allen, Only Yesterday, 288.

27.   Richard Karlgaard, “The Ghost of Netscape,” The Wall Street Journal, August 9, 2005, A10.

28.   Allen, Only Yesterday,273–274.

29.   Mike Snow, “Day-Trade Believers Teach High-Risk Investing,” The Washington Post, July 6, 1998.

30.   Chancellor, Devil Take the Hindmost, 210.

31.   Alexander Dana Noyes, The Market Place (Boston: Little, Brown and Company, 1938), 323–324.

32.   Lionel Laurent, “What Bitcoin Is Really Worth May No Longer Be Such a Mystery,” https://www.bloomberg.com/news/features/2018-04-19/what-bitcoin-is-really-worth-may-no-longer-be-such-a-mystery, accessed July 25, 2018.

CHAPTER 10

1.   Jonathan Cheng, “Mom and Pop Run with the Bulls,” The Wall Street Journal, March 29, 2013.

2.   Ibid.

3.   Ilia D. Dichev, “What Are Stock Investors’ Actual Historical Returns? Evidence from Dollar-Weighted Returns,” American Economic Review 97:1 (March 2007): 384–401; Thomas Dvorak, “Timing of Retirement Plan Contributions and Investment Returns: The Case of Defined Benefit Versus Defined Contribution,” The BE Journal of Economic Analysis & Policy 12:1 (2012): 1–24.

4.   Jay Ritter, “The Long-Run Performance of Initial Public Offerings,” The Journal of Finance 46:1 (March 1991): 3–27; and Ilia Dichev, personal communication.

5.   Benjamin Roth, The Great Depression: A Diary (New York: Public Affairs, 2009), vii–xxiv.

6.   Ibid., 44.

7.   Matthew Josephson, The Robber Barons (New York: Harcourt, Inc., 1934), 177. Thanks to Professor Richard Sylla for pointing this quote out.

8.   Alexander Pope, The Works of Alexander Pope Vol. IX (London: John Murray, Ablemarle St., 1866), 20.

9.   John Carswell, The South Sea Bubble (London: The Crescent Press, 1961), 191.

10.   Schwed, Where Are the Customers’ Yachts?, 155.

11.   Carswell, South Sea Bubble, 221–259. On the brief imprisonments, Andrew Odlyzko, personal communication.

12.   Richard S. Lambert, The Railway King (London: George Allen & Unwin Ltd., 1964), 207.

13.   Francis, History of the English Railway, II:195–196.

14.   John Kenneth Galbraith, The Great Crash 1929 (Boston: Houghton Mifflin Company, 1988), 99.

15.   Liaquat Ahamed, Lords of Finance (New York: Penguin, 2009), 231.

16.   Martin Gilbert, Winston S. Churchill (Boston: Houghton Mifflin Company, 1977), V:333–351, quote 350.

17.   Galbraith, Great Crash 1929, 99–119.

18.   Roth, The Great Depression: A Diary, 15,17.

19.   Bruce Barton, “Is There Anything Here that Other Men Couldn’t Do?” American Magazine 95 (February, 1923): 128, quoted in Susan Estabrook Kennedy, The Banking Crisis of 1933 (Lexington KY: The University Press of Kentucky, 1973), 113–114.

20.   The proportion began to rise again, slowly at first, and then with the stock market’s increasing popularity, more rapidly. Currently, it stands at 52% of all households.

21.   “The Death of Equities: How Inflation Is Destroying the Stock Market,” BusinessWeek, August 13, 1979; extensive quotations with the generous permission of Bloomberg Inc.

22.   Jason Zweig, “Lessons and Ideas from Benjamin Graham,” https://jasonzweig.com/lessons-and-ideas-from-benjamin-graham-2/, accessed March 29, 2022.

CHAPTER 11

1.   Benjamin Graham and Jason Zweig, The Intelligent Investor (New York: HarperBusiness Essentials, 2003), 8.

2.   Keith E. Stanovich and Richard F. West, “Individual Differences in Reasoning: Implications for the Rationality Debate?” Behavioral and Brain Sciences 23 (2000): 645–726.

3.   Paul Meehl, Clinical Versus Statistical Prediction (Northvale, NJ: Jason Aronson, Inc., 1996).

4.   Philip E. Tetlock, Expert Political Judgment (Princeton, NJ: Princeton University Press, 2005), 15.

5.   Amos Tversky and Daniel Kahneman, “Judgment Under Uncertainty: Heuristics and Biases,” Science 185:4157 (September 27, 1974): 1124–1131.

6.   Ibid., 1124.

7.   Kurt Vonnegut, Cat’s Cradle (New York: Delta Trade Paperbacks, 1998), 182.

8.   Andrew Coors and Lawrence Speidell, “Exuberant Irrationality: Judging Financial Books by Their Covers,” Journal of Behavioral Finance 7:4 (2006): 186–192.

9.   Jay R. Ritter, “The Long-Run Performance of Initial Public Offerings,” The Journal of Finance 46:1 (March 1991): 3–27.

10.   William J. Baumol, “Unnatural Value: Or Art Investment as Floating Crap Game,” American Economic Review 76:2 (May 1986): 10–14, quote 14.

11.   Baba Shiv, et al., “Investment Behavior and the Negative Side of Emotion,” Psychological Science 16 (June 2005): 435–439.

12.   Shlomo Benzarti and Richard H. Thaler, “Myopic Loss Aversion and the Equity Premium Puzzle,” Quarterly Journal of Economics 110:1 (January 1995): 73–92.

13.   Jeremy Siegel, Stocks for the Long Run (New York: McGraw-Hill, 2007), 124–125; Jay R. Ritter, “Economic Growth and Equity Returns,” working paper, November 1, 2004; Elroy Dimson et al., Triumph of the Optimists (Princeton, NJ: Princeton University Press, 2002), 156.

14.   Larry Speidell, et al., “Dilution Is a Drag . . . the Impact of Financings in Foreign Markets,” The Journal of Investing 14:4 (Winter 2005): 17–22; William J. Bernstein and Robert D. Arnott, “The Two-Percent Dilution,” Financial Analysts Journal 59:5 (September–October 2003): 47–55.

15.   Tetlock, Expert Political Judgment, 42–88, 98, 125–141, quote 63.

16.   Jason Zweig, The Devil’s Financial Dictionary (New York: Public Affairs, 2015), 229.

17.   Elroy Dimson, et al., Credit Suisse Global Investment Returns Yearbook (Summary), 2013, 24–27.

18.   Barna Research, “Americans Describe Their Views About Life After Death,” https://www.barna.com/research/americans-describe-their-views-about-life-after-death/, accessed April 11, 2022.

19.   Arnold C. Cooper, et al., “Entrepreneurs’ Perceived Chances of Success,” Journal of Business Venturing 3:2 (Spring 1988), 97–108, quote 107.

20.   Terry Odean, personal communication.

21.   Karl Marx and Frederick Engels, Selected Works 3:1 (Moscow: Progress Publishers, 1969), 163.

22.   David Swensen, Pioneering Portfolio Management (New York: The Free Press, 2000); Rick Ferri, “The Curse of the Yale Model,” Forbes.com, April 16, 2012, http://www.forbes.com/sites/rickferri/2012/04/16/the-curse-of-the-yale-model/.

23.   Niall Ferguson, The Ascent of Money (New York: Penguin Press, 2008), 329–330.

CHAPTER 12

1.   John Templeton, “Ten Principles of Investment Success,” https://www.franklintempleton.com.sg/resources/investor-education/investing-101/ten-principles-to-investment-success, accessed April 18, 2022.

2.   See https://www.dropbox.com/s/m33yj3t2iis02gh/Improving_Judgments_of_Existential_Risk_16march%202022.pdf?dl=0; also Philip Tetlock, personal communication.

3.   Simon Croom, et al., “Personality Differences and Buyer-Supplier Relationships: Psychopathy in Executives, Gender Differences and Implications for Future Research,” Journal of Purchasing and Supply Management 27:4 (October 2021): 1–10.

4.   See, for example, Reeves Wiedeman, Billion Dollar Loser (New York: Little Brown and Company, 2020).

5.   Miller, Plain Speaking, 147.

CHAPTER 13

1.   Sendhil Mullainathan, et al., “The Market for Financial Advice: An Audit Study,” NBER Working Paper Series, 17929, March 2012.

2.   Fred Schwed, Where Are the Customers’ Yachts? (Hoboken, NJ: John Wiley & Sons, 2006), 140.

3.   Joseph Nocera, A Piece of the Action (New York: Simon & Schuster, 1994), 34–52, 117–118.

4.   For a tour d’horizon of the “bad old days” of the brokerage industry (i.e., before about 2010), see Anonymous and Timothy Harper, License to Steal (New York: HarperBusiness, 1999). See especially 64–73 on principal transactions.

5.   Serena Ng and Thomas Gryta, “New Wall Street Conflict: Analysts Say ‘Buy’ to Win Special Access for Their Clients,” The Wall Street Journal, January 19, 2017; Robert Shiller, Irrational Exuberance (Princeton NJ: Princeton University Press, 2015), 49.

CHAPTER 14

1.   Gerald C. Fischer and Lawrence C. Minet, “No-Load Mutual Funds: An Analysis of Their Performance and Expense Ratios,” Financial Analysts Journal 20:1 (January–February 1964): 64–68.

2.   Ibid.; Bernstein, The Four Pillars of Investing (New York: McGraw-Hill, 2002), 204.

3.   Nocera, A Piece of the Action, 293–296.

4.   Russel Kinnel, “Mind the Gap: How Good Funds Can Yield Bad Results,” Morningstar FundInvestor 13:11 (July 2005): 1–3.

5.   Christopher Franz and Anthony Thorn, “Buy the Unloved 2022 Edition,” https://www.morningstar.com/articles/1075110/buy-the-unloved-2022-edition.

6.   Bernstein, The Four Pillars of Investing, 205.

7.   Eric Balchunas, The Bogle Effect (Dallas, TX: Matt Holt Books, 2022), 45–68; Samuelson quote from Jason Zweig, “What You Can Learn from One of Warren Buffett’s Smartest Investors,” The Wall Street Journal, December 21, 2018.

8.   Balchunas, Bogle Effect, 58.

9.   John C. Bogle, The Man in the Arena (Hoboken, NJ: John Wiley & Sons, Inc., 2013), 159–166; John C. Bogle, Don’t Count on It! (Hoboken, NJ: John Wiley & Sons, Inc., 2011), 375–376.

10.   Jonathan Clements, personal communication.

11.   Adam Sabban, “U.S. Fund Flows Smashed Records in 2021,” https://www.morningstar.com/articles/1075161/us-fund-flows-smashed-records-in-2021; “World’s Top Asset Management Firms,” https://www.advratings.com/top-asset-management-firms.

12.   Burton G. Malkiel, “Is Indexing Worse than Marxism?” The Wall Street Journal, November 14, 2016.

13.   Standard & Poor’s Indices Versus Active Funds Scorecard, Year End 2008, https://www.spglobal.com/spdji/en/documents/spiva/spiva-us-year-end-2008.pdf.

14.   Gus Sauter, personal communication.

15.   https://data.worldbank.org/indicator/CM.MKT.TRAD.CD.

16.   John C. Coates, “The Future of Corporate Governance Part I: The Problem of Twelve,” https://corpgov.law.harvard.edu/wp-content/uploads/2019/11/John-Coates.pdf.

17.   Balchunas, The Bogle Effect, 159–162.

18.   Kenneth Reinker and Edward Tower, “Index Fundamentalism Revisited,” http://public.econ.duke.edu/Papers//Other/Tower/Index.pdf.

CHAPTER 15

1.   Jane Bryant Quinn, “When Investment Writing Becomes Soft Porn,” Columbia Journalism Review (March–April 1998): 48–49.

2.   Anonymous, “Confessions of a Former Mutual Funds Reporter,” Fortune, April 29, 1999.

3.   See https://www.worldatlas.com/articles/which-are-the-biggest-industries-in-the-united-states.html and Helaine Olen, Pound Foolish (New York: Penguin, 2013), 24–25.

4.   John Cassidy, dot-con (New York: Penguin Press, 2002), 166.

5.   Gabriel Sherman, The Loudest Voice in the Room (New York: Random House, 2014), 146–147; Aaron Heresco, Shaping the Market: CNBC and the Discourses of Financialization (PhD thesis, Pennsylvania State University, 2014), 81, 151.

6.   Ekaterina V. Karniouchina, et al., “Impact of Mad Money Stock Recommendations: Merging Financial and Marketing Perspectives,” Journal of Marketing 73 (November 2009): 266–246; J. Felix Meschke, “CEO Interviews on CNBC,” working paper, http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.203.566&rep=rep1&type=pdf, accessed November 12, 2016.

7.   Howard Kurtz, The Fortune Tellers (New York: The Free Press, 2000), 206–207.

8.   The full url for the boglehead wiki is https://www.bogleheads.org/wiki/Main_Page.

CHAPTER 16

1.   Thomas Stanley and William Danko, The Millionaire Next Door (New York: Pocket Books, 1996). For a criticism of the book’s methodological flaws, see Nassim Taleb, Fooled by Randomness (New York: Random House, 2008), 143–146.

CHAPTER 17

1.   Charles D. Ellis, “The Loser’s Game,” Financial Analysts Journal 31:4 (July–August 1975): 19–20.

2.   For a lucid explanation of this, see Bill Jones, “Do Not Dollar Cost Average for More than Twelve Months,” http://www.efficientfrontier.com/ef/997/dca.htm. For a similar analysis of value averaging, see Simon Hayley, “Value Averaging and How Dynamic Strategies Bias the IRR and Dynamic IRR,” https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1606347.

3.   William J. Bernstein, The Intelligent Asset Allocator (New York: McGraw-Hill Inc., 2000), 138.

CHAPTER 18

1.   Anne Tergesen, “The Lawyer on a Quest to Lower Your 401(k) Fees,” The Wall Street Journal, June 9, 2017.

2.   Allan S. Roth, “Does Schwab’s Growth Threaten Vanguard’s Domination?” Financial Planning, January 20, 2020; and Allan S. Roth, personal communication.

3.   Schwab accepts PFOF for stocks and ETFs, while Vanguard and Fidelity do not. (Fidelity does accept PFOF for options trading.) See Tara Siegel-Bernard, “Yes, You Can Get Free Trading. But There’s Often a Catch,” The New York Times, November 29, 2019.

INDEX

Page numbers followed by f and t refer to figures and tables, respectively.

Active funds, 233–234

Actively managed funds, 237

The Ages of the Investor (Bernstein), 121

Ailes, Roger, 243–244

Aislabie, John, 166

Allen, Frederick Lewis, 157

AllianceBernstein, 65

Allocation:

of assets (see Asset allocation)

of bonds, 81, 111, 119, 123, 196

foreign, 120

of stocks (see Stock allocation)

Amazon, 6, 39–40, 155, 207

American National Bank, 231

Amsterdam Stock Exchange, 139

Anchoring, 184

Ancillary stock asset classes, 119, 121–123, 127

Annuities, 149

commercial, 106

deferred, 112–113

fixed indexed, 223

French government, 148

immediate fixed, 108–109

inflation adjusted, 105–106

variable, 228–229

Apple, 139, 186

ARK Innovation ETF, 65

ARK Investment Management, 65

“ARKK: An Object Lesson in How Not to Invest” (Arnott), 65

Arnott, Amy, 65

Asset allocation, 79–130

dynamic, 268–269

in retirement, 17, 109

risk tolerance for, 106

strategies for, 123–124, 259–263

taxes and, 294

Assets, confiscation of, 48, 50–51, 176, 209

Atterbury, Francis, 164

Authorized participants (APs), 234

Availability heuristic, 184, 188

Avantis, 122, 128, 286

Avantis Emerging Markets Value Fund, 287

Avon, 229

Ayres, Ian, 102–103

Baa bonds, 33

Babylonian Code of Hammurabi, 134

Bachelier, Louis, 56–57, 62, 80, 84

Back-loaded shares (Class B), 226

Bacon, Francis, 146–147, 154

Bagehot, Walter, 152

Balchunas, Eric, 230, 275

Bank of England, 139, 145, 153, 165–166

Banque Royale, 150

Banz, Rolf, 42

Barclays Aggregate Bond, 199

Barsky, Robert B., 104–105

Bartiromo, Maria, 244–245

Baruch, Bernard, 64, 143

Batterymarch, 231

Baumol, William, 186

Bear Stearns, 67

Bengen rule, 106–107

Berkshire Hathaway, 72–76, 73f, 84, 163

Bernanke, Ben, 83, 103

Berry, Michael, 42

Birkin bag, 197–198

Bitcoin, 158

Black Monday, 169

Black Thursday, 168–169

BlackRock, 126, 233–234, 277–278

Bloom, Sylvia, 1–3, 9, 27

Bloomberg, 80, 246, 275

Blunt, John, 166

Bodie, Zvi, 30, 102, 254, 306

Bogle, John C. (Jack), 57, 73, 219, 229–234, 245–246

Boglehead podcast, 243

The Bogleheads’ Guide to Investing, 263

The Bogleheads’ Guide to Retirement Planning, 247

Bonds:

asset-backed, 294

corporate (see Corporate bonds)

duration of, 192

high-yield, 229

index fund, 126, 223, 232, 259, 263, 294

intermediate, 82f, 90

mortgage, 209

municipal (munis), 50, 122, 129, 219, 236, 294, 299t

mutual fund, 294, 295t

prices of, 90

returns on, 4, 28, 30, 33–35, 50

Treasury (see Treasury bonds)

Boston Globe, 231

Boston University, 103

Boyle, Robert, 146

BRIC nations, 189

BrightScope, 274

Brokers, 215–223

Brooks, John, 66

Brownian motion, 56

Bubble Act, 150, 166

Bubble companies, 149–150

Bubbles, 132

cryptocurrency, 146

ingredients of, 148

Minsky’s criteria for, 165

1920s stock market, 152–153

origin of, 145–147

railway, 166–167

real estate, 301

South Sea Company, 149–150

spotting, 155–158

See also Dot-com (Tech) bubble; Financial Panics, Manias

Bucket shops, 218

Buffett, Warren, 3, 58, 70–77, 84, 163–164, 241

Burn rates, 106–114, 163

definition of, 4

inflation-adjusted, 32, 32f

during retirement, 251–252, 270–272

variation in, 125

Burr, Richard, 83, 103, 176

BusinessWeek, 173–177

“Buy the unloved” strategy, 228

Buybacks, 27*

“Can Stock Market Forecasters Forecast?” (Cowle), 57, 59

CAPE (see Cyclically adjusted P/E ratio)

Carnegie Mellon University, 187

Carswell, John, 164–165

Cassidy, John, 243–244

Caterpillar, 39–40

CDs (certificates of deposit):

in brokerage accounts, 128

emergency use of, 255

liquidity vs, 49, 122–123

as safe asset, 8, 113, 158, 209, 294, 305

as unimpaired capital, 163

Central Securities Corporation, 75–76

“Challenge to Judgment” (Samuelson), 56, 229

Chamberlain, Lawrence, 170

Chancellor, Edward, 164, 246

Charles Mackay, 154, 156

Chase National Bank, 168

Cheng, Jonathan, 161

Chicago Tribune, 57

China, 28, 51, 189

Churchill, Winston, 153, 168, 249

Cisco, 157

Clements, Jonathan, 67, 231, 245–246

Closed-end funds (CEFs), 234

CNA Financial Corporation, 66

CNBC, 155, 159, 188, 190, 243–245, 244f

CNN, 244

Coates, John C., 234

Columbia Business School, 71

Columbia Journalism Review, 241

Common Sense on Mutual Funds (Bogle), 243

Compound interest, 2, 22, 144, 305

“Confessions of a Former Mutual Funds Reporter,” 242

Congoleum, 71

Consumer price index (CPI), 33, 53, 189

Contango, 36, 52, 90–91, 129

Corporate Bonds (Corporates), 125–126, 300f

ETF-held, 236, 294

interest rates effect on, 33–35

intermediate-term, 80–83, 82f

loss rates for, 34f

mortgage bonds vs, 209

safety of, 50

stockholder effect on, 122

transaction fees for, 219

volatility of, 9

Correlations, 86–91, 88f, 98

Countrywide, 67

Cowles, Alfred, 3rd, 57–58, 61, 63, 69, 208

Cowles, Alfred, Sr., 57

Cramer, Jim, 244–245

The Crash of 1979, 185

Credit Suisse, 27–28, 195

Crown Cork & Seal, 71

CRSP index, 30–31, 42, 47, 53, 81, 281

Cryptocurrency, 37, 125, 132, 146, 176, 301

Currency, 37, 89, 93, 154

company issued, 148

gold-backed, 136

Curry, Stephen, 77

Cyclically adjusted P/E ratio (CAPE), 193–194, 193f, 194f, 268–269

Dahle, Jim, 247

Danko, William, 254

Data mining, 48, 58, 87

DCA (Dollar cost averaging), 261, 264–265

“The Death of Equities,” 173

Deep risk, 49–52, 209

Defined compensation (DC) plan, 273

Deflation, 51–52, 166, 209, 258

Depardieu, Gerard, 51

Devastation, 51, 166, 209

Devil Take the Hindmost (Chancellor), 164, 246

DeVoe, Raymond, Jr., 191

Dimensional Fund Advisors (DFAs), 44, 122, 128, 229, 235, 273

Dimson, Elroy (see DMS)

Dimson, Marsh, and Staunton (DMS), 27

Direxion Daily Agribusiness Bear 3x Shares (COWS), 236

Discount rates, 21–23, 166

Disney, 173

Diversification, 87–88, 91–93, 122, 278

of PMEs, 129

of real estate funds, 37

of stocks, 306

of tax, 263

Dividend yield, 21–27, 139, 193, 195, 269, 304

Dividends, 4–6, 20–27, 36, 112–114, 139, 269, 283

average annual payout from, 14

buyback effect on, 27*

from fixed indexed annuities, 223

during Great Depression, 171–175

from international investments, 189

from railway stocks, 151–152, 166

from REITs, 128, 262–263

for RLE, 271

during tilts, 171–175, 286

DMS (Dimson, Marsh, and Staunton), 27, 30, 36

Dodd, David, 170, 246

Dodge & Cox, 237

Dollar cost averaging (DCA), 261, 264–265

Dot-com (Tech) bubble, 46, 128, 143–144, 157–158, 193, 220, 227, 263 (See also Bubbles)

Double-bottoms, 59

Dow 36,000 (Glassman and Hassett), 21–22, 185

Dow Jones Industrial Average, 59, 68, 173, 176, 188

during 1929 stock market crash, 169

daily price changes of, 85f

fluctuations in, 170f

Dow Jones Real Estate Index, 301

Drawdowns, 107, 108f

Dreman, David, 42

Duke University, 23, 48, 237

E.A. Pierce and Cassatt, 218

East India Company, 139, 145

Econometrica, 57, 69

Economist magazine, 243, 245–246

Edleson, Michael, 261

EF Hutton, 68

Efficient market hypothesis (EMH), 28, 47, 76

Fama’s development of, 59

Samuelson’s support for, 72

skepticism of, 70

stock bubbles vs, 155

three types of, 59*

Einstein, Albert, 2, 56, 80, 144

Ellis, Charles, 231, 245, 258

Energy stocks, 119, 127–129, 260, 286, 291

Enron, 33–34

Equanimity, 4, 8

Equity(-ies), 40, 55

allocation of, 102, 112–114, 270, 286–287

bond performance effect on, 81, 123

buybacks and, 27*

contango and, 90

currency fluctuations and, 89

“death of,” 173–177

ETF assets, 234–235

foreign, 126–128, 189

funding business through, 18–19, 32, 138–139

history of, 114–115

losses during market declines, 84, 103, 192, 271

Monte Carlo and, 109

as percentage of portfolios, 37, 98, 119, 198, 266

precious metal, 128–129, 263, 291

private, 221

returns on, 20, 27, 74, 91, 270

risks of, 104–105

stability of, 52

stock performance effect on, 120–122, 161–163, 303

total stock market funds and, 278

Equity premium puzzle, 48

Equity risk premium (see Risk premium)

Ernst, Harry, 58, 195

Exchange traded funds (ETFs), 7, 44, 126, 213–214, 232, 275–277

as DFA products, 273

in diversified portfolios, 210, 221, 257–258

as index funds, 234–236

open-end funds vs, 281

tilted, 287

treasury, 294

Exchequer, 153, 166, 168

Expected returns, 23–27

in 2023, 35–37

of bonds, 33–35

as entertainment, 185–186

of equities, 20

fear and, 187

of foreign stocks, 120

of REITs, 204

of stocks, 20–21, 39–48, 106, 261, 293

See also Fundamental returns; Realized returns

Facebook, 20, 42, 207, 214

Factor zoo, 47–48, 58

Fama, Eugene, 195, 208

collaboration with French, 42–45, 47–48, 74

as creator of EMH, 155–156, 231

and Mandelbrot, 80, 84

Fama-French US Large Value and Growth indices, 53

Fannie Mae, 71

FDIC, 163, 294

Federal Reserve, 64, 76, 173

interest rate movement of, 137, 153–154

monetary tightening by, 90, 106–107

survey by, 170

Fermat, Pierre de, 148

Ferri, Rick, 243

Fidelity, 70–71, 75, 214, 231–233, 236, 275–278

Fidelity Capital Fund, 65–66

Fidelity Fund, 65

Fidelity Management and Research Company, 65

Fidelity Salem Street Trust, 71

Fidelity Select Technology Fund, 226–227

FIIT (First Index Investment Trust), 231

Financial Analysts Journal, 230–231

Financial News Network (FNN), 243

Financial Panics, 2–3, 68, 83, 102–102, 122–123, 147, 163–164 (See also Bubbles; Manias)

Financial Planning magazine, 228

Financial Times, 243, 245

First Index Investment Trust (FIIT), 231

Fisher, Irving, 57, 138, 158, 246

Fortune magazine, 242

401(k)s, 83, 259–264, 273–275

choosing funds for, 125

contributions to, 252–253

withdrawals from, 255

See also Roth 401(k)s

Fractional reserve banking, 145–146, 148, 154

Francis, John, 150

French, Kenneth, 42, 44–48, 74, 245, 306

Friedman, Milton, 56

Front-loaded shares (Class A), 226

FTSE Global All Cap Index, 120

FTSE Index, 128, 283

Fuller, Russell, 40

Fundamental returns, 24–25 (See also Expected returns; Realized returns)

“The Future of Corporate Governance Part I: The Problem of Twelve” (Coates), 234

Galbraith, John Kenneth, 168

Galton, Francis, 64

Garzarelli, Elaine, 68, 206

Gates, Bill, 241

General Electric (GE), 20, 206

Gensler, Gary, 217*

George I, King, 166

Glassman, James, 21–22

Glass-Steagall Act (1933), 172, 218, 231

Global Crossing, 167

Goetzmann, William, 156, 158

Goldman Sachs, 5, 225

Gordon equation, 22–23, 25–27, 25f, 26f, 185, 205–206

Graham, Benjamin, 5, 170–171, 203–204, 208–209, 246

on cheap stocks, 176

collaboration with Harvey, 5

on investor irrationality, 182

on IPOs, 186

Warren Buffet employment with, 71–72

Graham, John, 69

Graham-Newman Corporation, 71

Granville, Joseph, 68–69, 206

Granville Market Newsletter, 68

Great Depression, 7, 40, 46, 50, 147

The Great Depression: A Diary (Ledbetter and Roth), 162

Growth stocks, 40–42, 44–45, 53, 121, 128, 305

Gunning the fund, 226–227

Halley, Edmond, 148

Harper, Timothy, 247

Harvard University, 65, 136, 199, 216, 234, 261

Harvey, Campbell, 48, 69, 209

Hassett, Kevin, 21–22

Head-and-shoulder patterns, 59

HealthShares Dermatology and Wound Care ETF, 236

Hedge funds, 197–200

Hewlett-Packard, 173

HFR global index, 199

High-yield bonds, 9, 35, 229 (See also Junk bonds)

Hillel, 99, 101, 119

History of investing, 133–140

Hooke, Robert, 146

Housel, Morgan, 243

“How to Invest in Mutual Funds. They’re the Safest, Surest Way to Invest in a Surging Market,” 226

How to Think About Money (Clements), 243

Huberts, Lex, 40

Hulbert, Mark, 68–69

Hyams, Paul, 2

Hyperinflation, 50, 52f, 197, 258 (See also Inflation)

I bonds, 52, 111

IBM, 66, 229

Ilmanen, Antti, 34, 125

Ilmanen risk, 34, 80, 120

Incubator funds, 70–71

Index funds, 234–237

Inflation:

adjustments for, 29f, 30–33, 31f, 102, 114

bonds and, 90

as cause of capital loss, 50–53

historical rate of, 14, 23–27, 137–140, 153, 173–176

natural resources stocks as hedge against, 122, 129

performance of stocks during, 53t

protection from, 109, 110–112

rate in Japan, 93

responding to, 257–260

during retirement, 252–253, 270–271

TIPS funds and, 257–260, 297t

See also Hyperinflation

Inflation-adjusted annuities, 105–106

Inflation-adjusted dollars, 105–106, 107f

Inflation-adjusted stocks, 192

Initial public offerings (IPOs), 6, 157, 162, 186, 207

Insull, Samuel, 5, 167, 206

Insurance, 222–223

The Intelligent Asset Allocator (Bernstein), 7, 14, 44, 269

The Intelligent Investor (Graham), 243

Interest rates:

correlation with bond prices, 90

effect on returns, 36, 137

in history, 133–135, 138, 147, 152–153

risk-free, 137f

International stocks, 27–29

Inverse funds, 236, 301

Investment and Speculation (Chamberlain), 170

Investment Company Act (1940), 172, 220–221, 225, 229

Investment pornography, 239–247

The Investor’s Manifesto (Bernstein), 36

Iowa University, 187

Ip, Greg, 196

IPOs (see Initial public offerings)

IRAs, 259, 263

benefits of, 223

brokerage, 102

early withdrawal from, 255

post-employment rollovers to, 275

during rebalancing, 268

TIPS IN, 111

IRS, 51, 111, 120, 255, 287

iShares, 128, 177, 283

iShares 0-3 Month Treasury Bond ETF (SGOV), 277, 281

Jacobellis v. Ohio, 156

Jensen, Michael, 60–62

John Deere, 185

Johnson, Edward C. (Ned), III, 65–66, 226, 231–233

Johnson, Samuel, 138

Johnson & Johnson, 84

Josephson, Matthew, 163–164

The Journal of Finance, 42, 62, 98

The Journal of Portfolio Management, 56

J.P. Morgan, 20, 157, 163, 168

Juniper Networks, 157

Junk bonds, 9, 35, 203–204 (See also High-yield bonds)

Junk-treasury spread (JTS), 204

Kahneman, Daniel, 182–184

Kaplan, Robert, 3

Kassen, Michael, 226–227, 242

Kemble, Fanny, 151

Keynes, John Maynard, 4, 175, 192

Kidd, Wilmot H., III, 75–77

Kindleberger, Charles, 145–146

Kinnel, Russell, 227

Kiplingers, 240

Kitces, Michael, 112

Kolmogorov, Andrey, 56

Ladders, 127–128 (See also TIPS ladders)

Lamont, Thomas, 168

LaQuinta, 71

Large-cap funds, 227, 236, 277, 281–284, 287

Large-cap stocks, 121, 265, 274

Law, John, 148–150, 156

LEAPS (Long-term equity anticipation securities), 102

Ledbetter, James, 162

Legg Mason Value Trust, 67

Leveraged funds, 236, 301

Levinson, Michael, 40

Lévy, Paul, 56

Liability matching portfolio (LMP), 111–116, 115f

License to Steal (Harper), 247

Lieber, Ron, 242

Lipper, Arthur, 66

Load funds, 226, 228

Lockshin, Jane, 1–2

Long-term capital management (LTCM), 1–5, 56, 194, 196, 203, 303

Long-term equity anticipation securities (LEAPS), 102

“The Loser’s Game” (Ellis), 231, 258

LTV, 66

Lynch, Peter, 70–73, 72f, 75, 77, 186

Mackay, Charles, 143–144

Mad Money, 244, 244f

Madoff, Bernie, 198

Magellan Fund, 70–71, 72f, 75, 186, 236

Magerman, David, 76

Malkiel, Burton, 245–246

Mandelbrot, Benoit, 80, 84

Manhattan Fund, 66, 226

Manias:

Dutch tulip, 144, 147, 154

explained, 153–159

railway stock, 151–152

real estate, 146

stock, 21

tech, 132

See also Bubbles; Financial Panics

Manias, Panics, and Crashes (Kindleberger), 145–146

Market bottoms, 129, 136, 161–177, 195, 261

Market factor, 42–43, 46, 74–75

Market tops, 143–160

Markowitz, Harry, 98–99

Marsh, Paul (see DMS)

Marx, Karl, 198

Masters in Business podcast, 243

McDonald’s, 173

MCRetire©, 109

Mean reversion, 110, 267

Mean variance optimization (MVO), 98–99

Mean-variance, 81–83, 82f, 84, 86, 97f

Medallion Fund, 76

Meehl, Paul, 183

Memoirs of Extraordinary Popular Delusions and the Madness of Crowds (Mackay), 143

Mercer, Robert, 76

Meriwether, John, 1

Merrill, Charles Edward (Charlie), 217–219

Merrill Lynch, 218–219

Merton, Robert C., 1, 9, 56, 102

Meta Platforms (see Facebook)

Metrick, Andrew, 69

Miller, William (Bill), 67, 77, 242

The Millionaire Next Door (Stanley and Danko), 254

Minsky, Hyman, 146–147, 150–152, 154, 165

Mississippi Company, 143, 148–149, 156

Mitchell, Charles, 168, 171–172

Momentum effect, 62

Money magazine, 226

Monte Carlo analysis, 109–110

Monte Vecchio fund, 134

Montgomery Ward, 157

Moody’s, 33–34

Morgan Stanley, 157

Morningstar, 97, 278, 283

ARKK study by, 65

“buy the unloved” strategy of, 228

diversified mutual funds of, 62, 63f

Kinnell study at, 227

tilting data from, 286

MSCI China index, 189

MSCI EAFE Index, 276, 283

MSCI index, 128

Mullainathan, Sendhil, 216

Multifactor Regression, 74–75

Munger, Charlie, 84, 125, 131

Musk, Elon, 241

Mutual funds, 225–234

Nalebuf, Barry, 102–103

Narratives, 64, 155, 176–177, 185

National Association of College and University Business Officers, 199

National Bellas Hess, 157

National City Bank, 168, 171–172

National Security Agency (NSA), 76

NBC, 243

Net asset value (NAV), 234, 236, 277

Netflix, 185

Netscape, 157

Neumann, Adam, 206

New York Stock Exchange, 68, 217

New York Times, 240, 242

New Yorker magazine, 244

Newton, Isaac, 146, 150, 155–156, 179

Nifty Fifty, 173, 229

Nightly Business Report, 243

1929 stock market crash, 5, 57, 92, 153, 167–169, 218, 225

No-load funds, 225–226, 229

Norman, Montagu, 153

Novum Organum Scientiarum, 146

Odean, Terry, 195

Olen, Helaine, 247

Omaha, NE, 71–72, 75

Ongoing load shares (Class C), 226

Open-end funds, 214, 235–236, 257–258, 276–278, 287

Option pricing, 1

Orléans, Duke of, 148

Overconfidence, 196–197

Pascal, Blaise, 148, 264–265

Paulson, Hank, 83

Payment for order flow (PFOF), 277

P/E (see Price-to-earnings ratio (P/E))

Pecora, Ferdinand, 172–173

Pfau, Wade, 112

Phips, William, 144–145, 147

Pioneering Portfolio Management (Swensen), 198

Planet Money, 243

Polaroid, 66, 173, 229

Ponzi schemes, 166

Pope, Alexander, 164

Portfolios:

liability matching, 110–111

model, 123–128

risk, 110–111

Pound Foolish (Olen), 247

Power law, 80, 85, 85f

Precious metals stocks, 127, 260, 286, 291

Precious metals, 90–91, 97, 119, 128–129, 145

Precious metals equity (PME), see Precious metals stocks

Precious Metals Equity Fund, 293

Prestiti, 134–135, 135f, 138–139, 204

The Price of Time (Chancellor), 243

Price/book ratio, 45–46, 74

Price-to-earnings ratio (P/E), 40–41, 173, 186, 193, 193f, 194f, 268–269

Primecap Fund, 236–237

Primerica, 66

Procter & Gamble, 84, 185

ProShares Ultra Real Estate ETF (URE), 301

The Psychology of Money (Housel), 243

Quantum Fund, 77

Quinn, Jane Bryant, 64, 241–242

A Random Walk Down Wall Street (Malkiel), 243

Rat hole problem, 176

Real estate investment trusts (REITs):

allocation to, 127–128

as ancillary asset classes, 119, 121–122

correlations of S&P 500 and, 88f

in diversified portfolios, 37, 87, 92, 266, 286

expected returns of, 204

fund choices for, 292t

holding, 261–263

leveraged, 301

returns of, 87f

in variable annuities, 229

Realized returns, 23–24, 30, 35–37, 293 (See also Expected returns; Fundamental returns)

Rebalancing, 87, 97, 128–129, 260–263, 265–269

Reg BI (best interest), 217

Regression analysis, 74

Reinker, Kenneth, 237

Relative risk aversion (RRA), 104

Renaissance Technologies, 76

Rentiers, 175

Report of Foreign Bank and Financial Accounts (FBAR), 51

Representativeness, 184, 188

Residual living expenses (RLE), 105, 111, 114, 252, 254–255, 270–271

Retirement calculators, 251–255

Retirement Portfolios (Zwecher), 113

Return(s), 69–73

on 30-year US Treasury bonds, 4

arithmetic, 16–17

Berkshire Hathaway trailing, 73f

of bonds, 4, 28, 30, 33–35, 50

correlations of, 86–90

on energy stocks, 128–129

geometric, 16–17

inflation-adjusted, 16–17

interest rates effect on, 36, 137

of international stocks, 28, 29f, 120

in LMPs, 113–116

market factors of, 74–75

Monte Carlo analysis of, 109–110

risk and, 13–15, 135

risk-adjusted, 123

security, 51

standard deviation of, 80–83, 97–99

during tilt, 120–121

Trinity study of, 106–107

Riksbank (Swedish), 154

Risk (see Volatility)

Risk aversion, 104–105, 188, 208–209

Risk depth (see Deep risk)

Risk portfolio (RP), 111–112

Risk premium, 13–17, 30, 139, 187

betting on, 121

definition of, 36

expected returns and, 19–20

of junk bonds, 204

tilting and, 287

of Treasury bills, 70

of Treasury bonds, 39, 191

visibility of, 48

volatility and, 91

Risk-free interest rates, 74–75, 137f

Ritholtz, Barry, 243

RLE (see Residual living expenses (RLE))

Rocket locomotive, 151

Roper, Barbara, 217*

Roth, Allan, 233, 277

Roth, Benjamin, 162–163, 176

Roth, Bill, 162

Roth, Daniel, 162

Roth 401(k)s, 263 (See also 401(k)s)

Roubini, Nouriel, 68, 206

Royal Society (London), 146

RRA (Relative risk aversion), 104–105

Russell 1000 Value Index, 74, 281

Russia, 50–51, 189

Saint Petersburg bourse, 30

Sales loads, 61, 225–226, 229

Salomon, Robert S., Jr., 174

Salomon Brothers, 1, 174

Samuelson, Paul, 56, 72–73, 102–103, 229–230, 306

Samuelson, William, 102

Samuelson/Merton life-cycle theory, 102

Sanford C. Bernstein & Co., 233

Santayana, George, 65, 131

Sauter, Gus, 234–235

Savage, Leonard Jimmie, 56

Savings glut, 138

Schlichter, Jerome, 274

Schmelzing, Paul, 136–137

Scholes, Myron, 1, 9, 56

Schwab, 214, 275–278

Schwab International (open-end) Index Fund, 276

Schwed, Fred, 59†, 103, 165, 217, 246, 305

Scudder, Stevens & Clark Balanced and Common Stock funds, 226

SD (see Standard deviation)

Securities Act (1933), 172, 218

Securities Act (1934), 172, 218

Security Analysis (Graham and Dodd), 170, 186, 246

Senate Committee on Banking and Currency, 172

Sequence-of-returns risk, 4, 32, 107, 111, 113

Shakespeare element of investing, 3, 194, 203–210, 264

Shammai, 99

Shanghai Stock Exchange, 30

Sharpe, William, 59–60, 62, 69, 229, 231, 245

Sharpe ratio, 191f

Shaw, D. E., 77

Shearson Lehman, 68

Shiller, Robert, 193, 193f, 194f, 306

A Short History of Financial Euphoria (Galbraith), 243

Siegel-Bernard, Tara, 242

“The Silent Road to Serfdom: Why Passive Investment Is Worse than Marxism” (Sanford C. Bernstein), 233

Simons, Jim, 76–77, 254

Simons’s Law, 76

Single premium immediate annuity (SPIA), 270–271

Small stock factor, 42, 74

Social security:

deferral of, 106–110, 112, 114, 125, 270–271

as percentage of expenses, 114, 252

Solnik, Bruno, 91

Sommer, Jeff, 242

Soros, George, 77

South Sea Company, 132, 139, 143, 149–150, 156–158, 164–167, 165f

S&P 500 and Bloomberg Aggregate Bond Index, 35t

S&P 500 index, 62, 65–69, 231–323

Berkshire Hathaway vs, 72f

bonds effect on, 122

Central Securities Corporation vs, 75–76

composition of, 276

correlations between intermediate Treasuries and, 89–90, 90f

as part of CRSP 1–10 index, 81

as element of CAPE calculation, 193

ETFs in, 276

false correlations and, 48

Fidelity Magellan vs, 71, 72f

Gordon equation and, 24, 27

inflation-adjusted, 114

market bottoms and, 175–176, 195

overvaluation of, 269

post-2008 gains of, 136, 161

REITs and, 87, 88f, 92, 266

tech market vs, 227

2008 bear market effect on, 4, 128

volatility in, 121

SPDR S&P 500 ETF (SPY), 281

SPIA (Single premium immediate annuity), 270–271

Standard deviation (SD), 42–43

of 5-year notes, 191

correlations vs, 86–88

as measure of volatility, 9

pluses and minuses of, 80–83

of randomly generated portfolios, 97–98

of stock prices, 84–86, 140

use in Monte Carlo analysis, 109–110

See also Volatility

Standard & Poor’s Depository Receipts (SPDR), 275

Stanford University, 187, 199

Stanley, Thomas, 254

Stanovich, Keith, 182

State Street (SPDR), 126, 233–234, 275, 277–278

Stationarity illusion, 193–195

Staunton, Mike (see DMS)

Stephenson, George, 151

Stewart, Potter, 156

Stock allocation, 111, 124–125, 196, 259–261, 268–270

foreign, 119

of retirees, 271

of total world stock market, 127

Stock asset classes, 120–122

Stock picking, 59, 68, 95, 210, 241, 304

Stock price(s), 123

analyzing, 186

behavior of, 84–86

bidding up, 220

bond prices and, 90

CEOs appearance and, 244

corrections and, 103

dividend yield of, 195

historical, 136, 155, 157, 267

inflating, 66–67

inflation’s effect on, 52

interest rates effect on, 52

momentum of, 47

1929 crash effect on, 57, 153

random movement of, 59

South Seas shares of, 149

2008 bear market effect on, 161

value averaging and, 261

Sunday Times (London), 68

Swensen, David, 198

Target-date funds, 124, 126, 259, 274

T-bills (see Treasury bills (T-bills))

Tech bubble (see Dot-com (Tech) bubble)

Templeton, John, 44, 205

Tesla, 139, 186, 207, 281

Tetlock, Philip, 183, 190, 205–206

Thaler, Richard, 182–183, 274

The Theory of Interest (Fisher), 243

Thinking, Fast and Slow (Kahneman), 183

TikTok, 245

Tilting, 120–121, 286–293

TIPS (see Treasury inflation-protected securities)

TIPS ladders, 106–109

deferring purchase of, 113

maturation of, 110

during retirement, 125, 294

SPIA vs, 270–271

See also Ladders; Treasury inflation-protected securities (TIPS)

Tower, Edward, 237

Transamerica, 229

Treasury bills (T-bills):

Berkshire Hathaway stock holdings of, 74–75, 84

company stock comparison to, 70

in diversified portfolios, 257–258

inflation’s effect on, 24, 137

ladders, 277

precious metals miners comparison to, 91

relation to overall market factor, 42–43

as safe asset, 8, 15, 24

yields of, 190

Treasury bonds (Treasuries):

duration of, 204

emergency use of, 255

5-year, 91, 98

intermediate-term, 80–83, 82f, 89, 90f, 95–96, 96f

liquidity of, 49

in LMPs, 111, 113

purchasing at auction, 126, 224, 276

during rebalancing, 266

risk premiums and, 39

as safe asset, 158, 209, 294

short-term, 122–123, 163

30-year, 21, 33–34

in tilted portfolio, 260

Treasury ladders vs, 258

volatility of, 9

yields of, 190

Treasury Direct, 111

Treasury inflation-protected securities (TIPS), 33, 52, 137, 304 (See also TIPS ladders)

Treynor, Jack, 59–60

Trinity Study, 106–107

Triumph of the Optimists (Dimson, et al), 27

Tsai, Gerald, 65–67, 77, 226, 241–242

Tufts University, 58

Tversky, Amos, 182–184

Twain, Mark, 62

Twitter, 214, 227, 245

Two bucket approach, 111

2009 momentum crash, 47–48

Unimpaired capital, 163–164

University of California, Berkeley, 76, 195

University of Chicago, 59

University of Rochester, 60

“Unnatural Value: Or Art Investment as Floating Crap Game” (Baumol), 186

U.S. Steel, 20, 168

US debt/GDP ratio, 108–109, 183

USS Scorpion, 64

Value averaging, 261–265, 262t, 270

Value spreads, 45f, 46t, 49, 128, 287

Value stock factor, 42, 43f

Value stocks, 40–47, 92, 207, 257–258

allocation of, 128

earnings for, 41f

growth stocks vs, 304–305

inflation effect on, 53

large-cap, 227

tilting to, 119–121, 286–287

twenty-year trailing returns of, 43f

underperformance of, 269

US small, 288t–289t

Warren Buffet preference for, 73

Vanguard 2030 Fund, 259

Vanguard Balanced Index Fund, 199

Vanguard Effect, 275

Vanguard ETFs, 199

Vanguard Group, 6–7, 126–128, 213–214, 221, 230–237, 273, 275–278

Vanguard International Stock Index Fund, 263

Vanguard Life Strategy Funds, 259

Vanguard Russell 3000 ETF, 281–283

Vanguard Short-Term Treasury Index Fund, 126

Vanguard S&P 500 Fund, 73, 281

Vanguard Target Retirement 2065 Fund (VLXVX), 124

Vanguard Total Bond Index Fund, 232

Vanguard Total Stock Market, 263

Vanguard Total Stock Market ETF (VTI), 235

Vanguard Total Stock Market Index Fund, 232

Vanguard/Transamerica, 229–237

Variable annuities, 228–233

Variance Drag, 16–17, 301

Variety(newspaper), 167

VIX (Chicago Board Options Volatility Index), 91

VLXVX (Vanguard Target Retirement 2065 Fund), 124

Volatility, 32, 169, 199

of currency, 89

definition of, 9

estimating, 137

options, 91

of PMEs, 129

random motion and, 56

SD as measurement of, 80, 83, 191

of stock market, 15, 59, 121

variance drag effect of, 17, 301

See also Standard deviation (SD)

Volcker, Paul, 30, 173

VTI (Vanguard Total Stock Market ETF), 235

VXX ETF, 91

Wall Street Journal, 67, 76, 161, 196, 242

Wall Street Week, 243

War of the Spanish Succession, 148

Warburg, Paul, 158

Washington Mutual, 67

Weimar hyperinflation (1920-1923), 52, 52f

Weisenberger Investment Companies, 231

Welch, Jack, 206

Wellesley Income Fund, 237

Wellington Management, 229–231

Wells Fargo, 231

West, Richard, 182

WeWork, 206

Whalen, Grover, 168

“Whales,” 210, 222

Where Are the Customers’ Yachts? (Schwed), 243, 246

White Coat Investor (Dahle), 247

Whitney, Richard, 168

Wiggin, Albert, 168

Williams, Serena, 70

Winnick, Gary, 167

Wood, Cathie, 65–66, 242

Xerox, 66, 173, 229

Yale University, 57, 198–199

Yield curve, 190–191, 206

Your Money and Your Brain (Zweig), 243

YouTube, 245, 306

Zillow.com, 209

Zuckerberg, Mark, 241

Zwecher, Michael, 113

Zweig, Jason, 230, 242, 245–246

ABOUT THE AUTHOR

William Bernstein is a retired neurologist and cofounder of Efficient Frontier Advisors, an investment management firm. He has produced several finance titles, including The Intelligent Asset Allocator, The Four Pillars of Investing, and The Investor’s Manifesto; and also four volumes of history, The Birth of Plenty, A Splendid Exchange, Masters of the Word, and The Delusions of Crowds about, respectively, the economic growth inflection of the early nineteenth century, the history of world trade, the effects of access to technology on human relations and politics, and the history and social psychology of mass manias.

He has also contributed to the peer-reviewed finance literature and has written for several national publications, including Money Magazine and The Wall Street Journal. He was the 2017 winner of the CFA Institute’s James R. Vertin Award.