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More Than You Know

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by Michael J Mauboussin




  Table of Contents

  Title Page

  Epigraph

  Dedication

  Acknowledgements

  Introduction

  Part 1 - Investment Philosophy

  INTRODUCTION

  Chapter 1 - Be the House

  Hit Me

  From Treasury to Treasure

  Prioritizing Process

  Chapter 2 - Investing—Profession or Business?

  The Scouting Report

  Evaluating the Winners

  The Investment Profession Versus the Investment Business

  Chapter 3 - The Babe Ruth Effect

  Batting with the Babe

  The Downside of Hardwiring

  Bulls, Bears, and Odds

  From OTC to OTB

  A Useful Analogy

  Chapter 4 - Sound Theory for the Attribute Weary

  Circumstance Over Attributes

  The Three Steps of Theory Building

  When, Not What

  Chapter 5 - Risky Business

  Rocket Science

  From Uncertainty to Probability

  How Predictions Change Future Payoffs

  Chapter 6 - Are You an Expert?

  Man Versus Machine

  Where Do Experts Do Well?

  Chapter 7 - The Hot Hand in Investing

  Finding the Hot Shot

  Streaks and Skill

  Toss Out the Coin Toss

  Streaks and Luck

  Chapter 8 - Time Is on My Side

  One or One Hundred

  Explaining the Equity-Risk Premium

  The Value of Inactivity

  Pictures Worth a Thousand Words

  Chapter 9 - The Low Down on the Top Brass

  Management Counts

  Leadership

  Incentives

  Capital Allocation

  The Bottom Line

  Part 2 - Psychology of Investing

  INTRODUCTION

  Chapter 10 - Good Morning, Let the Stress Begin

  Why Zebras Don’t Get Ulcers

  Why Money Managers Do Get Ulcers

  Shortening Horizons

  Imitating Ulysses

  Chapter 11 - All I Really Need to Know I Learned at a Tupperware Party

  A Tip from Shining Shoes

  You Can Fool Mother Nature

  All I Really Need to Know . . .

  The Psychology of Investing

  Chapter 12 - All Systems Go

  Emotions and Decisions

  Two Follows One

  The Affect Heuristic

  When the Experiential Fails

  Affect: Individual Versus the Collective

  Chapter 13 - Guppy Love

  Guppy See, Guppy Do

  Feedback—Negative and Positive

  Follow the Ant in Front of You

  Herding from the Grapevine

  Chapter 14 - Beware of Behavioral Finance

  Sorry Syllogism

  Mug’s Game?

  Bombs Away

  Money See, Money Do

  Chapter 15 - Raising Keynes

  What Do You Expect?

  Speculation and Enterprise

  Visiting El Farol

  Kidding Yourself

  Chapter 16 - Right from the Gut

  Guns and Better (Decisions)

  Chopping Down the Decision Tree

  Investing au Naturel

  The Fine Print

  Chapter 17 - Weighted Watcher

  I Do—Do You?

  Sifting Weights

  Misleading by Sample

  Tell Me Something the Market Doesn’t Know

  Part 3 - Innovation and Competitive Strategy

  INTRODUCTION

  Chapter 18 - The Wright Stuff

  Take Off with Recombination

  How Does Wealth Happen?

  Sic Itur ad Astra (This Is the Way to the Stars)

  Creative Destruction—Here to Stay

  Chapter 19 - Pruned for Performance

  Too Clever by Half

  The Dynamics of Innovation

  Investors: Use the Brain

  Chapter 20 - Staying Ahead of the Curve

  Losing Pride

  Goldilocks Expectations: Too Cold, Too Hot, Just Right

  Out with the Old, In with the New

  The Mind Makes a Promise That the Body Can’t Fill

  Expectations and Innovation

  Chapter 21 - Is There a Fly in Your Portfolio?

  Fruit Flies and Futility

  Speed Trap?

  Investor Evolution

  Chapter 22 - All the Right Moves

  Managing for the Long Term

  Deep Blue’s Lessons

  Strategies for Winners

  Strategy as Simple Rules

  Chapter 23 - Survival of the Fittest

  A Peek at Another Peak

  Fitness Landscapes

  Look Before You Leap?

  Tools of the Trade-Off

  Chapter 24 - You’ll Meet a Bad Fate If You Extrapolate

  Social Versus Security

  Nonstationarity and Historical P/Es

  Why the Past May Not Be Prologue

  Bounded Parameters

  Unpacking the (Mental) Baggage

  Chapter 25 - I’ve Fallen and I Can’t Get Up

  Returns and Growth

  Death, Taxes, and Reversion to the Mean

  I’ve Fallen and I Can’t Get Up

  Chapter 26 - Trench Cooperation

  The War Metaphor—Death or Life?

  Why a Date and a Marriage Are So Different

  Price and Quantity

  Chapter 27 - Great (Growth) Expectations

  Compounding and Confounding

  Reality Check

  The Bigger They Are, the Slower They Grow (or Don’t Grow)

  Refuse Refuge in Castles in the Air

  Part 4 - Science and Complexity Theory

  INTRODUCTION

  Chapter 28 - Diversify Your Mind

  Ant Brain

  A-Mazing

  Getting a Diversity Degree

  Creativity and Investing

  Chapter 29 - From Honey to Money

  Smart Ant

  Traveling Salesman? Follow the Ant . . .

  Delphic Decision Markets

  The Stock Market—the Ultimate Hive?

  Swarm Smarts

  Chapter 30 - Vox Populi

  The Accuracy of Crowds

  Needle in a Haystack

  Weighing the Ox with the Vox

  Estimating Printers with Populi

  And Now, For the Real World

  Chapter 31 - A Tail of Two Worlds

  Experience Versus Exposure

  Tell Tail

  What Fat Tails Mean for Investors

  Chapter 32 - Integrating the Outliers

  Bernoulli’s Challenge

  What’s Normal?

  St. Petersburg and Growth Stock Investing

  Integrating the Outliers

  Chapter 33 - The Janitor’s Dream

  Beyond Newton

  Sorting Systems

  The Stock Market as a Complex Adaptive System

  Using What You’ve Got

  Chapter 34 - Chasing Laplace’s Demon

  Evolution Made Me Do It

  Laplace’s Demon

  Interpreting the Market

  Investor Risks

  Chapter 35 - More Power to You

  Zipf It

  The More Things Change . . .

  Catch the Power

  Chapter 36 - The Pyramid of Numbers Firm Size, Growth Rates, and Valuation

  Why Big Fierce Animals Are Rare

  Find Your Niche

  Dear CEO: We’ve Made It to the Fortune 50! You’re Fired

&nbs
p; Extrapolative Expectations

  Chapter 37 - Turn Tale

  Hush Puppies and Dogs of the Dow

  Ah Choo

  Economists, Meet Mr. Market

  No Progress in Human Nature

  Maintain Perspective

  Chapter 38 - Stairway to Shareholder Heaven

  I Could Do That

  Stairway to Shareholder Heaven

  Making the Art Less Abstract

  Order and Disorder

  Conclusion

  NOTES

  References

  Further Reading

  INDEX

  Copyright Page

  A balanced perspective cannot be acquired by studying disciplines in pieces but through pursuit of the consilience among them. Such unification will come hard. But I think it is inevitable. Intellectually it rings true, and it gratifies impulses that rise from the admirable side of human nature. To the extent that the gaps between the great branches of learning can be narrowed, diversity and depth of knowledge will increase.

  —Edward O. Wilson, Consilience

  To my parents

  Who always stood behind me but were never too close

  ACKNOWLEDGMENTS

  I wrote the original versions of these essays while I was at Credit Suisse (formerly Credit Suisse First Boston). In my dozen years at CSFB, management consistently offered me marvelous opportunities for professional development. Allowing me to launch The Consilient Observer—the offbeat offering that provided the basis for More Than You Know—is a tribute to the firm’s open-mindedness and support. In particular, I am indebted to Brady Dougan, Al Jackson, Terry Cuskley, Steve Kraus, and Jim Clark. Credit Suisse was also gracious in granting me the copyrights to these works.

  Two names were listed on The Consilient Observer’s original masthead. The other belonged to my research associate, Kristen Bartholdson, who made significant contributions in research, editing, number crunching, and producing exhibits. She also helped update material for this edition. Smart and talented, Kristen is also a delightful person to work with.

  Dan Callahan, my research associate at Legg Mason Capital Management, picked up where Kristen left off, working tirelessly on all aspects of this book. He was instrumental in updating the material for both editions, getting the exhibits and manuscript in shape, and coordinating all communication. Dan is resourceful, productive, and bright. He’s also a great guy, and I’m really pleased he is on my team.

  All of my coworkers at Legg Mason Capital Management have been terrific, providing valuable support and cooperation. LMCM also allowed me to use copyrighted material. Thanks to all of you.

  Two people have had a major professional influence on me. The first is Al Rappaport, with whom I wrote Expectations Investing. I have learned an enormous amount from Al, and he remains a tremendous source of inspiration and constructive feedback.

  The other is Bill Miller, whom I now have the honor of calling a colleague. Bill stimulated many of the ideas in these essays, either directly or indirectly. It’s one thing to write about how the mental-models approach helps investors, it’s quite another to use the approach to generate excess returns. Bill has done both, and for that he deserves all of the admiration he receives.

  Both Al and Bill have always been gracious with their time, and have taught me with patience. They are great role models, and I feel privileged to be associated with both of them.

  These essays draw from the work of many fabulous scientists, too many to list individually. But a handful of thinkers deserve special mention, including Clayton Christensen, Paul DePodesta, Norman Johnson, Scott Page, Jim Surowiecki, and Duncan Watts. Thanks to each of you for sharing your ideas with me so generously. Steve Waite’s suggestions were also of great benefit to me.

  I’d like to thank Myles Thompson, my publisher and editor at Columbia University Press, for his boundless enthusiasm and unwavering belief in the power of these ideas. Assistant editor Marina Petrova has also been an immense help in all aspects of the project. Michael Haskell improved the book’s flow with his thoughtful edits and supplied the new, comprehensive title. Nancy Fink Huehnergarth was instrumental in shaping the original manuscript, providing both valuable editorial input and a fantastic sense of humor.

  I also appreciate Sente Corporation’s very talented Jay Smethurst and Bryan Coffman for their artistic contributions. They were with me from the very beginning of the consilient journey. At CSFB, Marian Toy and Ann Funkhouser were great editors to work with: efficient, constructive, and thoughtful. My administrative assistant at CSFB, Melissa Little, also helped in key areas such as exhibit production and distribution.

  My wife, Michelle, is a constant source of love, support, and counsel. My mother-in-law, Andrea Maloney Schara, is the rare grandmother who can explain systems theory and throw a football. Finally, I thank my children Andrew, Alex, Madeline, Isabelle, and Patrick for allowing me to see diversity firsthand.

  INTRODUCTION

  More Than You Know’s core premise is simple to explain but devilishly difficult to live: you will be a better investor, executive, parent, friend—person—if you approach problems from a multidisciplinary perspective. It’s the difference between moving into a fixer-upper home with a full set of power tools versus a simple screwdriver. You are going to be a lot more successful and efficient if you have the proper tool for each job at hand.

  The reality is that the majority of us end up with pretty narrow slices of knowledge. Most occupations encourage a degree of specialization, and some vocations, like academia, insist on it. And there are the time constraints. We are all so busy talking on the phone, answering e-mails, and going to meetings that we don’t have any time left to read, think, and play with ideas.

  Following the publication of this book’s first edition, a lot of readers contacted me to say they enjoyed the exposure to non-traditional ideas. Most people easily appreciate the value of diverse thinking. But many readers view diversity as something that’s nice to have, not something that’s essential to success. In contrast, I have come to believe cognitive diversity is crucial to solving complex problems.

  The case for cognitive diversity is based on theory and practice. In his book The Difference, social scientist Scott Page demonstrates the logic of diversity. He shows, using mathematical models, how and why diversity is necessary to solve certain types of problems. Page deftly nudges the diversity discussion away from metaphor and anecdote toward grounded, timeless theorems.

  Notwithstanding Page’s theoretical contribution, you might ask whether there’s any actual evidence for diversity’s value in predicting the outcomes of complex problems. The answer, a resounding yes, is based on psychologist Phil Tetlock’s remarkable research summarized in his book Expert Political Judgment. Tetlock asked hundreds of experts to make thousands of predictions about economic and political events over a fifteen-year span. He then did something quite rude. He kept track of their results.

  Expert forecasters were, on balance, deeply unimpressive. But Tetlock found some were better than others. What separated the forecasters was how they thought. The experts who knew a little about a lot—the diverse thinkers—did better than the experts who knew one big thing.

  Two sources in particular have inspired my thinking on diversity. The first is the mental-models approach to investing, tirelessly advocated by Berkshire Hathaway’s Charlie Munger. The second is the Santa Fe Institute (SFI), a New Mexico-based research community dedicated to multidisciplinary collaboration in pursuit of themes in the natural and social sciences.

  Charlie Munger’s long record of success is an extraordinary testament to the multidisciplinary approach. For Munger, a mental model is a tool—a framework that helps you understand the problem you face. He argues for constructing a latticework of models so you can effectively solve as many problems as possible. The idea is to fit a model to the problem and not, in his words, to “torture reality” to fit your model.

  Certain character traits encourage the mental-mode
ls method to blossom. Fortunately, these are mostly traits you can choose: intellectual curiosity, integrity, patience, and self-criticism. Problem-solving success is not just a matter of IQ. As Munger notes, the great naturalist Charles Darwin’s worldview-changing results reflect more his working method than his raw intellect. On the flip side, examples abound of smart people making bad decisions, often showing inflexibility or a failure to appreciate psychology’s lessons.

  A mental-models approach does not come without a cost, though. You need to spend substantial time and effort learning about various disciplines. Without a doubt, too, your learning may not be useful right away (in fact, it may never be useful). The good news is there are typically only a few big ideas in each discipline that you’ll need to master.

  I have learned a great deal from Munger’s musings over the years, and his influence is clear throughout these pages. Fortunately, Peter Kaufman assembled Munger’s background and speeches in Poor Charlie’s Almanack, a terrific book offering plenty of insight on the mental-models approach.

  The Santa Fe Institute sprung from a group of like-minded scientists who decided the world needed a new kind of academic institution. These scientists, each distinguished in his field, recognized that universities often operate in academic isolation; professors spend a lot of time with colleagues in their field but rarely cross disciplinary boundaries. The founders felt strongly that much of the fertile scientific ground was between disciplines, and they were determined to cultivate it. Spend some time at SFI’s campus and you are likely to see physicists, biologists, and economists all chiming in with their diverse perspectives on a topic of interest.

  The unifying theme at SFI is the study of complex systems. In both the physical and social sciences, lots of systems emerge from the interaction of many heterogeneous parts. Examples include human consciousness, the immune system, and the economy. SFI scientists were early in identifying the salient features of these systems and in considering the similarities and differences across disciplines.

  The SFI-inspired idea that has most deeply influenced me is viewing the stock market as a complex adaptive system. Embracing this mental model compelled me to revisit and question almost everything I learned in finance: agent rationality, bell-shaped price-change distributions, and notions of risk and reward. I believe the complex-adaptive-systems framework is not only a much more intuitive way to understand markets but also more consonant with the empirical record.

 

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