Adaptive markets financial evolution at the speed of thought

I call this new way of thinking the multiple roles that evolution plays in shaping human behavior and fi nancial markets, and “hypothesis” is meant to connect and contrast markets mean t

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Introduction 1

Chapter 1 Are We All Homo economicus Now? 12

Chapter 2 If You’re So Smart, Why Aren’t You Rich? 45

Chapter 3 If You’re So Rich, Why Aren’t You Smart? 75

Chapter 4 The Power of Narrative 102

Chapter 5 The Evolution Revolution 135

Chapter 6 The Adaptive Markets Hypothesis 176

Chapter 7 The Galapagos Islands of Finance 222

Chapter 8 Adaptive Markets in Action 249

Chapter 10 Finance Behaving Badly 330

Chapter 12 To Boldly Go Where No Financier

FINANCIAL FEAR FACTOR

Fear is a wonderful thing Several years ago, an airline pilot named

mag-azines But as soon as he entered the store, he turned around and walked right out He did so because he felt an overwhelming sense of fear At

store and was shot and killed Only aft erward— with some thoughtful debriefi ng by Gavin de Becker, personal security expert and bestselling

that may have triggered his fear: a customer wearing a heavy jacket spite the hot weather; the clerk’s intense focus on that customer; a car

omp-son’s decision to leave the store came almost instantaneously, long before

he was even aware that he had observed anything out of the ordinary.Our fear is a precision instrument Neuroscientists have shown that our fear refl exes are highly refi ned, and that we react much faster out

of fear than our conscious mind is able to perceive When physically threatened, our “fi ght or fl ight” response— marked by increased blood pressure, faster refl exes, and a rush of adrenaline— has helped keep our

But it turns out that the same neural circuits are oft en triggered when we’re threatened in other ways— emotionally, socially, and fi nancially— and therein lies the problem While the fi ght or fl ight response might have some benefi ts in contexts other than bar fi ghts and war zones, it almost surely won’t help you when the stock market crashes and your

has been shaped by hundreds of thousands of years of evolution, in response to predators and other environmental threats Money has only been around for a few thousand years, a blink of an eye on the

evolutionary timescale Stock markets are an even more recent human

invention Homo sapiens hasn’t had time to adjust to the new realities of

modern life and that poses certain challenges— and opportunities— for investors, portfolio managers, and the rest of us

We need a new way of thinking about fi nancial markets and human behavior, and that’s what this book is about I call this new way of thinking

the multiple roles that evolution plays in shaping human behavior and

fi nancial markets, and “hypothesis” is meant to connect and contrast

markets mean that there’s no such thing as a free lunch, especially on Wall Street: if fi nancial market prices fully incorporate all relevant in-formation already, trying to beat the market is a hopeless task Instead, you should all put your money into passive index funds that diversify

as broadly as possible, and stay invested in stocks for the long run Sound

it was taught to your broker, your fi nancial adviser, and your portfolio manager In 2013, University of Chicago fi nance professor Eugene F Fama was awarded the Nobel Prize in Economic Sciences specifi cally

inves-tors and fi nancial markets behave more like biology than physics, prising a population of living organisms competing to survive, not a collection of inanimate objects subject to immutable laws of motion

that the principles of evolution— competition, innovation, reproduction, and adaptation— are more useful for understanding the inner workings

of the fi nancial industry than the physics- like principles of rational nomic analysis It implies that market prices need not always refl ect all available information, but can deviate from rational pricing relations from time to time because of strong emotional reactions like fear and greed It implies that market risk isn’t always rewarded by market re-turns It implies that investing in stocks in the long run may not always

eco-be a good idea, especially if your savings can eco-be wiped out in the short run And it implies that changing business conditions and adaptive responses are oft en more important drivers of investor behavior and

market dynamics than enlightened self- interest— the wisdom of crowds

is sometimes overwhelmed by the madness of mobs

con-trary, fi nancial economics is still among the most highly sought- aft er

fi elds of expertise on Wall Street (especially if the starting salaries of fi

sub-sides and is replaced by the wisdom of crowds— at least until the next shock disrupts the status quo From the adaptive markets perspective,

like the parable of the fi ve blind monks who encounter an elephant for the very fi rst time Being blind from birth, they have no idea what this strange creature is, but when one monk feels the elephant’s leg, he con-cludes “an elephant is just like a tree,” and when another monk feels the trunk, he disagrees, saying “an elephant is just like a snake,” and so on Each monk’s impressions are technically correct, but they all miss the bigger picture We need a better theory

investors have had a chance to adapt to existing business conditions, and those conditions remain relatively stable over a long enough pe-riod of time If the previous sentence sounds like the fi ne print of an insurance policy, it should; business conditions oft en shift violently and “long enough” depends on a lot of things For example, between October 2007 and February 2009, imagine if you had your entire nest egg invested in the S&P 500, a well- diversifi ed portfolio of fi ve hun-dred of the largest U.S.- based companies You would have lost about

51 percent of your life savings over those seventeen stressful months

As you watched your retirement evaporate a few percentage points each month, at what point would your “fear factor” have kicked in and caused you to cash out?

While our fear refl exes may protect us from injury, they do little to prevent us from losing large sums of money Psychologists and behav-ioral economists agree that sustained emotional stress impairs our ability

to make rational decisions Fear leads us to double down on our mistakes rather than cutting our losses, to sell at the bottom and buy back at the top, and to fall into many other well- known traps that have confounded most small investors— and not a few fi nancial professionals Our fear makes us vulnerable in the marketplace

Th at’s why we need a new, more complete framework for thinking about fi nancial markets, one that incorporates the fear factor as well as rational behavior In the same way that no blind monk is able to fi gure out the elephant by himself, we need to piece together insights from multiple disciplines to get the full panoramic picture of how fi nancial markets work and why they fail.

I’ll be taking you on the same intellectual journey I’ve traveled over the course of my academic career to arrive at the Adaptive Markets Hy-pothesis It’s not a straight road to this destination— at times we’ll take brief excursions into other disciplines, including psychology, evolution-ary biology, neuroscience, and artifi cial intelligence— but these excursions

con-tradiction between the academic perspective of rational markets and the behavioral evidence to the contrary Rather than accepting one view and rejecting the other, it’s possible to reconcile these two opposing per-spectives within a single consistent adaptive framework

We’ll need to know something about how the brain works, how we make decisions, and crucially, how human behavior evolves and adapts, before we can understand bubbles, bank runs, and retirement planning Each of the disciplines we’ll draw on is a blind monk, unable to provide

us with a complete theory, but when taken as a whole, we’ll see the phant in sharp focus

ele-DON’T TRY THIS AT HOME

Many of us have felt fear individually when faced with the power of fi nancial markets, but 2008 was the year the global fi nancial crisis gave

Brothers went belly up, stock markets around the world plunged in response, and individual retirement accounts were savaged It didn’t matter if you held 60 percent stocks and 40 percent bonds, or 30 percent stocks and 70 percent bonds: you lost more money than you were pre-

hit in 2008 were those lucky few who happened to be invested in U.S government bonds or cash— and a few hedge fund managers Ending the year on a fi nal bad note, December 2008 brought us the Madoff

scandal, a Ponzi scheme of such epic proportions, it made the original Charles Ponzi look like a rank amateur 2008 was the year that inves-tors learned to fear the market once more.

Why were we so unprepared? In part, because we were told it couldn’t

prices fully refl ect all available information Popular investment gurus told us to forget about trying to beat the market and to forget about re-

might as well throw darts at the fi nancial pages to pick our stocks, cause we’d end up doing just about as well as the professionals, if not better We should buy and hold a passive, well- diversifi ed portfolio of stocks and bonds, they said, preferably through a no- load index mutual fund or an exchange- traded fund, requiring as little thought as possi-

always takes everything into account

profes-sional money managers, but the basic idea is more than forty years old

“wisdom of crowds” in his delightful book of the same name, turning

Decades of academic research have argued, and argued convincingly, that trying to beat the market is a fool’s errand Any pattern or regular-ity in asset prices in the market would immediately be taken advantage

of by investors looking to make a profi t, leaving behind only random

fl uctuations in their wake Investors made a market that’s perfectly

ef-fi cient And if that was the case, why not simply ride the tide? Not only did this idea garner a Nobel Prize for Fama, but it was also the motiva-tion for today’s multi- trillion- dollar index fund industry

Burton Malkiel, in his bestselling 1973 book, A Random Walk Down Wall Street, fi rst popularized the Effi cient Markets Hypothesis, to give the theory its formal name, to the investor Malkiel, an economist at Princeton, told us that the paths followed by stock prices over time re-sembled a drunkard’s walk—meandering, erratic, and unpredictable—hence the book’s title Malkiel made the obvious conclusion: if stock prices followed random walks, then why pay a professional money manager? Instead, he advised readers to put their money in broadly

diversifi ed, passive mutual funds that charged minimal fees— and lions of his readers did.

mil-In a curious twist of fate, a former Princeton undergraduate launched

a mutual fund company for this exact purpose a year aft er Malkiel’s book debuted You may have heard of this individual, the index fund pioneer John C Bogle His little startup, the Vanguard Group, manages over $3 trillion and employs more than fourteen thousand people as of

oft en dispensed to millions of consumers, is “don’t try this at home.” Don’t try to beat the market Instead, stick to passive buy- and- hold in-vestments in broadly diversifi ed stock index funds, and hold these investments until you retire

Still, there’s no shortage of examples of investors who did and do beat the market A few well- known portfolio managers have routed it deci-sively, like Warren Buff ett, Peter Lynch, and George Soros But have you ever heard of James Simons? In 1988, this former professor started

a fund trading futures using his own mathematical models In its fi rst eleven years, Simons’s Medallion Fund racked up a 2,478.8 percent net

fund was closed to new investments aft er that point, so less is known

of its subsequent performance, but in 2016, Forbes estimated Simons

to be worth $15.5 billion, having made $1.5 billion in 2015 Simons didn’t get rich investing in index funds How does this jibe with market

THE GREAT DIVIDE

Aft er 2008, the wisdom of fi nancial advisers and academics alike seemed naive and inadequate So many millions of people had faithfully invested

did the fi nancial crisis wound one’s professional pride more deeply

economists On one side of the divide were the free market economists, who believe that we are all economically rational adults, governed by the law of supply and demand On the other side were the behavioral

economists, who believe that we are all irrational animals, driven by fear and greed like so many other species of mammals.

your views on gun control (unnecessary), consumer protection laws veat emptor), welfare programs (too many unintended consequences), derivatives regulation (let a thousand fl owers bloom), whether you should invest in passive index funds or hyperactive hedge funds (index funds only), the causes of fi nancial crises (too much government inter-vention in housing and mortgage markets), and how the government should or shouldn’t respond to them (the primary fi nancial role for gov-ernment should be producing and verifying information so that it can

(ca-be incorporated into market prices)

war One of the fi rst casualties was the former Federal Reserve man Alan Greenspan, the man who journalist Bob Woodward called the “Maestro” in his biography of that name published in 2000 As the chairman of the Federal Reserve Bank from 1987 to 2006, Greenspan was one of the most respected central bankers in history, serving an un-precedented fi ve consecutive terms, strongly supported by Democratic and Republican presidents alike In 2005, economists and policymak-ers from around the world held a special conference at Jackson Hole,

and Ricardo Reis determined that, “while there are some negatives in the record, when the score is toted up, we think he has a legitimate claim

Greenspan was a true believer in unfettered capitalism, an unabashed disciple and personal friend of philosopher- novelist Ayn Rand, whose philosophy of Objectivism urges its supporters to follow reason and self- interest above all else During his tenure at the Fed, Greenspan actively

fi nancial crisis humbled him Before the House Committee on sight and Government Reform on October 23, 2008, while the crisis was happening in real time, Greenspan was forced to admit he was wrong:

to protect shareholders’ equity, myself included, are in a state of shocked

disbelief.”7 In the face of the fi nancial crisis, the rational self- interest of the marketplace failed catastrophically.

breadth, and duration of the recent crisis suggest that many mists, policymakers, regulators, and business executives also got it wrong How could this have happened? And how could it have happened to

econo-us, here in the United States, one of the wealthiest, most advanced, and most highly educated countries in the world?

“IT’S THE ENVIRONMENT, STUPID!”

Financial markets are a product of human evolution, and follow biological

natural selection that determine the life history of a herd of antelope also apply to the banking industry, albeit with somewhat diff erent pop-ulation dynamics

Economic behavior is but one aspect of human behavior, and human behavior is the product of biological evolution across eons of diff erent environments Competition, mutation, innovation, and especially nat-ural selection are the basic building blocks of evolution All individuals are always vying for survival— even if the laws of the jungle are less vicious

on the African savannah than on Wall Street It’s no surprise, then, that economic behavior is oft en best viewed through the lens of biology

human population growth would increase exponentially, while food plies would increase only along a straight line He concluded that the human race was doomed to eventual starvation and possible extinction

sup-No wonder economics became known as the “dismal science.”

technological innovations which greatly increased food production— including new fi nancial technologies like the corporation, international

trade, and capital markets However, he was among the fi rst to appreciate the important relationship between human behavior and the economic environment To understand the complexity of human behavior, we need to understand the diff erent environments that have shaped it over time and across circumstances, and how the fi nancial system functions under these diff erent conditions Most important, we need to understand how the fi nancial system sometimes fails Academia, industry, and pub-lic policy have assumed rational economic behavior for so long that we’ve forgotten about the other aspects of human behavior, aspects that don’t fi t as neatly into a mathematically precise framework.

Nowhere is this more painfully obvious than in fi nancial markets Until recently, market prices almost always seemed to refl ect the wis-dom of crowds But on many days since the fi nancial crisis began, the collective behavior of fi nancial markets might be better described as the

mar-kets, oscillating between wisdom and madness, isn’t a pathology It’s simply a refl ection of human nature

Our behavior adapts to new environments— it has to because of evolution— but it adapts in the short term as well as across evolutionary time, and it doesn’t always adapt in fi nancially benefi cial ways Finan-cial behavior that may seem irrational now is really behavior that hasn’t

from nature is the great white shark, a near- perfect predator that moves

million years of adaptation But take that shark out of the water and drop it onto a sandy beach, and its fl ailing undulations will look silly and irrational It’s perfectly adapted to the depths of the ocean, not to dry land

Irrational fi nancial behavior is similar to the shark’s distress: human

be-tween the irrational investor and the shark on the beach is the shorter length of time the investor has had to adapt to the financial envi-ronment, and the much faster speed with which that environment is changing Economic expansions and contractions are the consequences

of individuals and institutions adapting to changing fi nancial ments, and bubbles and crashes are the result when the change occurs too quickly In the 1992 election, Democratic strategist James Carville

environ-prioritized matters succinctly for Clinton campaigners: “Th e economy, stupid!” I hope to convince you that biologists should be reminding economists, “It’s the environment, stupid!”

REVENGE OF THE NERDS

ignored by fi nancial economists until recently, and understandably so For the past fi ft y years, academic fi nance has been dominated by highly mathematical models and methods that have much more in common

unprecedented wave of innovation in fi nance, just as they did in ics Sophisticated quantitative models, pioneered by academics and the academically trained, quickly spread throughout the fi nancial industry

toolkit for traders, bankers, risk managers, and even regulators

What you knew became more important than who you knew And for the

fi rst time in modern history, the graduates of MIT and Caltech found themselves more employable on Wall Street than the graduates of

mathemati-cal language of the Street— alpha, beta, mean- variance optimization, and the Black- Scholes/Merton option- pricing formula— were given great sta-tus and even greater compensation It was the revenge of the nerds.But any virtue can become a vice when taken to an extreme, and the mathematization of fi nance was no exception Finance isn’t physics, despite the similarities between the physics of heat conduction and the

physicist Richard Feynman, speaking at a Caltech graduation ceremony, once said, “Imagine how much harder physics would be if electrons had

man-agers, and regulators do have feelings, even if those feelings were mostly disappointment and regret during the last few years Financial econom-ics is much harder than physics

Warren Buff ett once referred to derivative securities as “fi nancial

understand-ing the risks of exotic fi nancial instruments But we can turn this

destruction, nuclear physics, is also responsible for many positive eries, such as nuclear power, magnetic resonance imaging, and anticancer radiation treatments

discov-How we choose to deploy these powerful technologies makes all the

we need the Adaptive Markets Hypothesis We need a new narrative to make sense of the wisdom of crowds, the madness of mobs, and evolu-tion at the speed of thought

Our search for this new narrative begins with a terrible catastrophe

If markets truly refl ect the wisdom of crowds, the market reaction to this catastrophe will illustrate just how wise crowds can be

Are We All Homo economicus Now?

TRAGEDY AND THE WISDOM OF CROWDS

At 11:39 a.m on Tuesday, January 28, 1986, the Space Shuttle Challenger

took off from the Kennedy Space Center at Cape Canaveral Seventy-

three seconds into its fl ight Challenger exploded Millions of people

around the world were watching live on television, many of them kids drawn by the presence of schoolteacher Christa McAuliff e, the Shuttle’s

fi rst civilian passenger It’s likely that the vast majority of Americans learned about the tragedy within an hour If you were watching, you probably still remember exactly where you were and how you felt at that moment

At fi rst no one knew what had happened At the fi rst press ence, held later that aft ernoon, NASA’s Associate Administrator for the Shuttle program Jesse W Moore said he would refuse to speculate on the causes of the disaster until a full investigation had taken place “It will take all the data, careful review of that data, before we can draw any

For the next few weeks, the only publicly available information on the disaster was a compilation of footage taken from the NASA video feed

few seconds of video Was it the large cylindrical fuel tank containing

the results are explosive: the classic case is the Hindenburg disaster A frame- by- frame analysis suggested that a fi re appeared there seconds before the explosion Perhaps the cause was a leak in a liquid oxygen line, or an explosive bolt misfi ring, or a fl ame burning through one of the solid booster rockets . .  Rumors abounded for weeks before NASA re-

Six days aft er the disaster, President Reagan signed Executive Order

12546 establishing the Rogers Commission, an impressive fourteen- member panel of experts that included Neil Armstrong, the fi rst person

to walk on the moon; Nobel Prize- winning physicist Richard Feynman; Sally Ride, the fi rst American woman in space; and legendary test pilot Chuck Yeager On June 6, 1986, a little over fi ve months aft er the disas-ter, aft er conducting scores of interviews, analyzing all the telemetry data from the shuttle’s fl ight, sift ing through the physical wreckage re-covered from the Atlantic Ocean, and holding several public hearings, the Rogers Commission concluded that the explosion was caused by the failure of the Shuttle’s now- infamous O- rings on the right solid fuel

rocket, rather like the gasket on a faucet However, when exposed to cold temperatures, rubber becomes more rigid, and it no longer provides

an effective seal Richard Feynman demonstrated this in a simple but unforgettable way at a press conference He dipped a perfectly

fl exible O- ring in ice water for a few minutes, took it out, and squeezed

was so cold that ice had built up on the Kennedy Space Center launch pads the night before— and the O- rings had apparently become stiff

con-tained the liquid oxygen and liquid hydrogen, also causing the booster rocket to break loose and collide with the external fuel tank, triggering the fatal explosion

nan-cial repercussions Four major NASA contractors were involved in the

have been a welcome relief for the other three companies cleared of sponsibility aft er fi ve months of fi nger pointing, investigation, and in-

Stock markets are merciless in how they react to news Investors buy

or sell shares depending on whether news is good or bad, and the ket will incorporate the news into the prices of publicly traded corpora-tions Good news is rewarded, bad news is punished, and rumors oft en

mar-have just as much impact as hard information But it usually takes the market time and eff ort to digest the news and factor it into stock prices

So we can ask a simple question: how long did it take for the market to

process the Challenger explosion and incorporate it into the stock prices

of the four NASA vendors? Was it a day aft er the release of the report?

A week?

In 2003, two economists, Michael T Maloney and J Harold herin, answered this question, and the result was shocking: the stock

Feynman’s brilliant live demonstration of the defective O- rings, but on

the accident (see fi gure 1.1) By 11:52 a.m., only thirteen minutes aft er the explosion, the New York Stock Exchange had to halt trading in Morton

dropped 6 percent, and by the end of the day it was down almost 12

stock prices of Lockheed, Martin Marietta, and Rockwell International also fell, but their drops and overall volume traded were much smaller, and within statistical norms

If you’re cynical about the ways of the stock market, you might

what had happened and began dumping their stocks immediately aft er the accident But Maloney and Mulherin were unable to fi nd any evi-dence for insider trading on January 28, 1986 Even more startling was the fact that the lasting decline in the market capitalization of Morton

incurred

What took the Rogers Commission, with some of the fi nest minds on the planet, fi ve months to establish, the stock market was able to do within a few hours How on earth could this have happened?

Markets Hypothesis Imagine the combined knowledge, experience,

Table 1.1.

Stock price movements and returns of the four major space- shuttle fi rms in the period

immediately surrounding the 11:39 a.m crash of the Space Shuttle Challenger on

January 28, 1986

Time Morton Th iokol Lockheed Martin Marietta

Rockwell International Panel A Stock price movements

11:30 a.m US$37.25 US$47.25 US$35.38 US$34.75

12:36 p.m US$35.00 US$45.00 US$32.50 US$34.13 1:00 p.m US$34.38 US$45.00 US$33.00 US$33.25 Panel B Stock returns

in that stock from 11:52 a.m to 12:44 p.m Th e fi rst postcrash trade in Morton Th iokol occurred at 12:36 p.m on NASDAQ.

Source: Maloney and Mulherin (2003, table 2).

Price relative to open Lockheed Martin Marietta

Rockwell Morton Thiokol

Figure 1.1. Intradaily stock price chart of the four major space- shuttle fi rms in the

period immediately following the 11:39 a.m crash of the Space Shuttle Challenger on

January 28, 1986, until the 4:00 p.m close Source: Maloney and Mulherin (2003,

fi gure 1) All four price series are normalized by their 11:40 a.m prices.

judgment, and intuition of tens of thousands of experts focused on just one single task: coming up with the most accurate estimate of the price

of a share of stock at a single point in time Now suppose that each of these

the more money these experts will make, and the faster they can move

in a nutshell

in an effi cient market, the price of an asset fully refl ects all available information about that asset But this simple statement has vast impli-

cations Somehow the stock market in 1986 was able to aggregate all

information about the Challenger accident within minutes, come up

with the correct conclusion, and apply it to the assets of the company that must have immediately appeared most likely to be aff ected More-over, the market was able to accomplish this without its buyers and sellers having any special technical expertise about aerospace disasters

A catastrophic explosion might suggest a failure in the fuel tanks, made

Challenger example certainly implies it is— the wisdom of crowds has

enormously far- reaching consequences

A RANDOM WALK THROUGH HISTORY

Markets are mysterious things to the layperson, and this is nothing new People have been trying to understand the behavior of markets for hun-dreds if not thousands of years Our fi rst records of money are at least four thousand years old, and although it’s impossible to say, schemes to beat the market were probably invented shortly thereaft er One ancient

on the island of Chios in anticipation of a large olive harvest When his prediction came true, he made a large profi t selling the use of the oil presses to the local olive growers, proving— according to Aristotle— that

“it is easy for philosophers to be rich if they choose, but this is not what

Money is a numerical concept When we want to see how much money we have, we count it Over time, people naturally developed new forms of mathematics to keep track of money As mathematics grew more sophisticated, investors began using these more advanced meth-

dif-ferent cultures For example, a still popular type of technical analysis

called candlestick charting, based on the geometry of historical price

graphs, was originally developed to analyze rice futures in Japan

One of the earliest mathematical models of fi nancial market prices

in-vesting and gambling both involve calculating trade- off s between risk

(Th e Book of Games of Chance), a textbook on gambling by the

promi-nent Italian mathematician Girolamo Cardano, who was also a opher, engineer, and astrologer— a classic Renaissance man Cardano off ered some very wise advice on speculation that we would all do well

gam-bling is simply equal conditions, e.g., of opponents, of bystanders, of money, of situation, of the dice box, and of the die itself To the extent

to which you depart from that equality, if it is in your opponent’s

a “fair game”— one that doesn’t favor you or your opponent— came to

wants to be a fool

mathematics and physics, but the important takeaway here is ingly simple In a fair game, your winnings or losses can’t be forecast by looking at your past performance If they could, then the game isn’t fair, because you could increase your bet when the forecast is positive, and

de-velop a slight edge over your opponents, and over time, you could put the profi ts from your slight edge back into the game, over and over, until

have fi gured out ways to predict the behavior of a deck of cards in jack, and the motion of the ball on a roulette wheel from its past perfor-mance, and they used that knowledge to make themselves a small for-

Now, imagine if you had a slight edge in predicting the behavior of the market, rather than the casino table Even the slightest edge would bring you tremendous amounts of wealth Over the years, many thou-sands of people have tried concocting systems to beat the market Most

with the names of overconfi dent investors who were humbled by the market And in 1900, a French mathematics Ph.D student believed he had discovered why

Louis Jean- Baptiste Alphonse Bachelier (1870– 1946) was a doctoral candidate at the Sorbonne under the great mathematician Henri Poin-caré As an undergraduate, Bachelier had studied mathematical phys-ics, but for his doctoral thesis, he chose to analyze the Parisian stock market, in particular the prices of warrants trading on the Paris Bourse

A warrant is a fi nancial contract that gives its owner the right, but not

assurance of buying at a fi xed price removes fi nancial uncertainty and gives the warrant owner additional fi nancial fl exibility

behaves before that crucial date

Bachelier discovered something very unusual about stock prices Many earlier researchers had tried to forecast patterns in the price movements of stock Bachelier saw that this method assumed an imbal-ance in the market Any stock trade has a buyer and a seller, but in order

to make a trade, they fi rst must agree on a price It has to be a fair trade:

no one wants to be a fool Aft er all, there’d be no agreement if one side were consistently biased against the other As a result, Bachelier con-cluded that stock prices must necessarily move as though they were com-pletely random

be something as simple as a coin fl ip In a fair game, past performance

is no guarantee of future outcomes Aft er each turn, you’ll either win some money (heads) or lose some money (tails) Now imagine playing

this fair game repeatedly, but with a twist Visualize your winnings and losses physically by taking a step forward or backward with every fl ip

of the coin (You might need to do this on a sidewalk, or in a hallway.)

precari-ous two- step dance, as you lurch back and forth like a drunk driver tempting to walk a straight line at a sobriety checkpoint Any fair game like a martingale will produce wins and losses in a random pattern like

at-a “drunkat-ard’s wat-alk”— at-and at-as Bat-achelier discovered, so do the prices in

the stock market Today, we call Bachelier’s discovery the Random Walk Model of stock prices.

Bachelier’s analysis was decades ahead of its time In fact, Bachelier anticipated Albert Einstein’s very similar work in physics on Brown-ian motion— the random motion of a tiny particle suspended in fl uid,

come up with a general theory of market behavior, and he did so by arguing that an investor could never profi t from past price changes Because the random price movements in a market were martingales, Bachelier concluded, “the mathematical expectation of the speculator was zero.” In other words, beating the market was mathematically impossible

Unfortunately, Bachelier’s work languished for years, and the reasons

eventually published in 1914 It was commended by the French tifi c establishment, but not extravagantly so Bachelier was denied tenure

scien-at the University of Dijon due to a negscien-ative letter of recommendscien-ation from the famous probability theorist Paul Lévy, aft er which Bachelier spent the rest of his career at a small teaching college in the town of

through the cracks because it was too avant- garde for the times— too much like fi nance for the physicists, and too much like physics for the

fi nanciers

implau-sible to be true It wasn’t until 1954 that Leonard Jimmie Savage, a prominent professor of statistics at the University of Chicago, acciden-tally came upon a copy of Bachelier’s thesis in the university library Savage sent letters to a number of his colleagues, alerting them to this

undiscovered gem One of the recipients was Paul A Samuelson, perhaps the most infl uential economist of the twentieth century It’s no exaggera-tion to say this letter changed the course of fi nancial history.

THE BIRTH OF EFFICIENT MARKETS

One major reason why modern economics is so mathematical is Paul

A Samuelson It’s almost impossible to list all the ideas in economics to which Samuelson fi rst gave mathematical form Every economist has a characteristic style, and Samuelson’s was deeply inspired by the Ameri-can mathematical physicist Josiah Willard Gibbs Samuelson applied ideas from physics across the full spectrum of economics, and econom-ics accepted them gratefully His 1941 Ph.D thesis, somewhat immod-

estly titled Foundations of Economic Analysis, immediately became a classic in the fi eld, and likewise his 1948 textbook, simply titled Eco- nomics, is still in print and in its nineteenth edition.17 Legendary for his quips and verbal wit, Samuelson won the Nobel Prize in 1970, surpris-ing absolutely no one Aft er a long and illustrious career reshaping eco-nomics in his image, Samuelson died in 2009, at the advanced age of ninety- four

But let’s return to the 1950s Samuelson immediately understood the signifi cance of Bachelier’s work aft er Savage alerted him to it Samuel-son turned his research focus to fi nance in the early 1960s, referring to

But if Bachelier explained the how of the Random Walk Model, elson set out to explain why market prices moved as though they were

Samu-random

Samuelson hit on the answer through his interest in a very practical problem in the Chicago futures market Every commodities trader on the Chicago fl oor knew there were patterns in the price of wheat Spot prices in wheat tended to rise from the fall harvest to the following spring due to storage costs, and then dropped immediately before the next harvest, when the market anticipated a future glut Changes in the weather also aff ected the price of wheat from day to day However, in

1953 the economist Maurice Kendall showed that wheat prices appeared

Samuelson spotted a paradox: if the weather infl uenced the price of

knew that weather patterns, while complicated, did not behave domly, and certainly the seasons didn’t follow each other randomly ei-ther It seemed to Samuelson that Bachelier’s Random Walk actually proved too much

characteristic of his personal style in economics Using the cal technique of induction, Samuelson showed that all the information

mathemati-of an asset’s past price changes are bundled in the asset’s present price

up to that point— changes in the weather, storage costs, etc Everything has already been taken into account As a result, past price changes

carry no information in predicting the asset’s next price.

Samuelson reasoned as follows If investors were able to incorporate all the potential impact of future events on an asset’s price today, then future price changes could not be predicted based on any of today’s information If they could, investors would have used that informa-

tion in the fi rst place As a result, prices must move unpredictably If a

the expectations of all the players in the market— then the following

price changes will necessarily be impossible to forecast It’s a subtle

idea, but it’s clearly related to Cardano’s martingale and Bachelier’s

summarizes his main idea: “Proof that Properly Anticipated Prices

Sam-uelson that he withheld publishing it for years SamSam-uelson later ted, “I must confess to having oscillated over the years in my own mind between regarding it as trivially obvious (and almost trivially vacuous)

alone Almost simultaneously, it was independently developed by the University of Chicago fi nance professor Eugene F Fama Fama was an unlikely student of fi nance, a tough third- generation Italian- American who excelled in sports in high school and majored in Romance languages

at Tuft s University in the late 1950s.23 In his words, Fama became “bored with rehashing Voltaire,” and took an economics course that changed his life By his last year at Tuft s, he was collecting daily data on the Dow Jones Industrial 30 to construct mathematical stock forecasting schemes Although the undergraduate Fama failed to fi nd a way to beat the market, data- driven statistical analysis would become a hallmark of Fama’s personal style in economics.

Fama continued his study of the stock market as a Ph.D student at the University of Chicago, one of the few universities then using modern digital computers in fi nancial research Fama found strong statistical evidence that stocks moved randomly Many random processes in na-ture have outcomes that come close to a “normal” distribution, also

known as a Gaussian distribution, but more popularly known as the bell

curve, due to its symmetrical, bell- like shape You might even have been graded on this curve by a particularly fearsome teacher: the top 2.5 per-cent of the class receiving an A, the next 13.5 percent receiving a B, the middle 68 percent receiving a C, the next lowest 13.5 percent receiving

a D, and the lowest 2.5 percent receiving an F is very close to a normal distribution Fama discovered that the distribution of stock returns could have far more outliers than would a normal, Gaussian distribu-tion Instead of a bell curve, the distribution of Fama’s stock returns

showed what are now known as fat tails, as though a teacher grading on

a curve gave the top 10 percent of students an A instead of the Gaussian

An “effi cient” market is defi ned as a market where there are large numbers

of rational, profi t- maximizers actively competing, with each trying to predict future market values of individual securities, and where impor-tant current information is almost freely available to all participants. . . 

In an effi cient market, on the average, competition will cause the full

eff ects of new information on intrinsic values to be refl ected neously” in actual prices.25

“instanta-Fama summarized his version of the Effi cient Markets Hypothesis in an

all available information.”

ultimately shook the entire fi nancial industry At the suggestion of Harry Roberts, one of his Chicago colleagues, Fama broke down mar-

infor-mation contained in past prices, so using past prices to forecast future price changes, such as “head- and- shoulders” patterns and candlestick charts in technical analysis, is useless

a company’s earnings, sales, and book- to- market ratios to pick stocks is also pointless

informa-tion can’t be used to generate profi table trading strategies

In one fell swoop, Fama dismissed the work of Wall Street’s cal analysts, fundamental analysts, proprietary traders, and hedge fund

techni-managers as a complete waste of time If prices already refl ected all able information, what was the point of hiring an industry analyst or a fund manager? No wonder Wall Street was so slow to embrace modern

avail-fi nancial economics

Over the years, Eugene Fama and his disciples unleashed a fl ood of

many times other researchers cite it One of Fama’s most highly cited publications was coauthored with Larry Fisher, Michael Jensen, and

simple but brilliant analysis captivated the academic fi nance nity, but it appalled Wall Street professionals, for reasons that are worth describing in some detail

perform controlled experiments to test ideas Economics has many

intricate theories, as complex as any within physics, but we can hardly put an entire economy in a laboratory and conduct experiments on it

As a result, economists have to rely on complicated statistical tests, looking for clear theoretical signals amidst the noise of reality, and we’re oft en frustrated in our attempts

But sometimes, we get lucky and come across “natural experiments”

in the raw data, where just one factor has changed in exactly the spot we

di-rectly, by comparing the baseline situation, the control group, versus the changed situation, the experimental group

Fama and company found such a natural experiment in the stock market, and it’s a particularly elegant one FFJR looked at the impact

of a stock split on the price of the stock A two- for- one stock split gives

changes nothing about the stock except for the price per share nies do it mainly to make the share price more aff ordable for the typical investor However, in the past, stock splits were oft en accompanied by an increase in dividends, most likely because the increase in stock price that motivated the split was due to a growing and successful business For that reason, a historical stock split should be considered good news about the company, and the stock price should rise in response to the split.FFJR looked at the prices of 940 stock splits from January 1927 to December 1959 and found two unmistakable regularities: stock prices

Compa-jumped up on the day that a split was announced, but showed no clear

stocks that split, presumably in anticipation of an increase in dividends, but the reward came almost instantly When the split actually happened,

on the other hand, the market couldn’t have cared less (If this analysis

reminds you a little of Maloney and Mulherin’s study of the Challenger

explosion, it should, because Maloney and Mulherin used the same statistical methods pioneered by Fama and his colleagues.)

FFJR concluded that stock prices fully refl ected all available mation on the day of the announcement of the stock split It was yet an-

impli-cation, yet another slap in the face to Wall Street practitioners And adding insult to injury, FFJR also showed that this regularity couldn’t

be exploited by trading on the announcement Only inside information could give you an edge in the market, which would be illegal— but re-

denied the eff ectiveness of insider trading Because of studies like this, FFJR’s coauthor Michael Jensen boasted in 1978 that “there is no other proposition in economics which has more solid empirical evidence sup-

Fama has become one of the most infl uential fi nancial economists of

Hypothesis has become at least as prominent a hallmark, thanks to Gene Fama

EFFICIENT MARKETS UNPACKED

Two economists with very dissimilar styles of thought, Paul Samuelson

Fama’s fascination with computers, data, and statistical analysis led him

Hypoth-esis than Samuelson’s elegant, simpleminded, physics- inspired version

ef-fi cient market of all is one in which price changes are completely dom and unpredictable, but it isn’t an accident of nature It’s the direct result of market participants attempting to profi t from their informa-

let’s try a thought experiment Suppose you happen to be an investor in

a coff ee- machine manufacturer, Koff ee Meister, which has just released

a new state- of- the- art compact cappuccino maker, the ’Cino Bambino Now suppose you also happen to be an expert in coff ee- machine design, and you decide to take the ’Cino Bambino out for a spin

Aft er considerable testing and engineering analysis, you conclude that this new line of coff ee machines has serious safety issues Reluctantly, you decide to sell your shares of Koff ee Meister in anticipation of the impending fallout when these fl aws become apparent to the market

shares before the safety issues become public knowledge may cause the market price to decline, thereby incorporating the essence of your anal-ysis into the price

Unless you own a signifi cant percentage of Koff ee Meister’s shares, however, your selling activity isn’t likely to have a lasting impact on the price Aft er all, individuals buy and sell shares of Koff ee Meister every day, and for many reasons But if you happen to be a big shareholder of Koff ee Meister stock (which may explain why you spent so much time and eff ort testing the ’Cino Bambino), your decision to sell may well hurt the share price

In fact, even if you didn’t own any shares of Koff ee Meister, you might still want to bet on the information you’ve acquired You can do this by short- selling Koff ee Meister Short sales are a little more complicated than the typical stock trade, but not much more You borrow shares of Koff ee Meister in order to sell them at a higher price, buy the shares back at a lower price (you hope) when you’re proven right, return the borrowed shares to the lender, and pocket the diff erence between the price you received for selling them and the price you paid to buy them back

And if other investors come to the same conclusion about Koff ee Meister’s safety issues, perhaps for diff erent reasons, they’ll likely sell their shares as well, in which case the cumulative impact on Koff ee Meister’s market price will be substantial Because of savvy investors like you, market prices act as a kind of average of the information and opinions of all market participants, weighted by the amount of money each participant is willing to commit to his or her convictions

wisdom of crowds Driven by enlightened self- interest (also known as greed), an army of investors will pounce on even the smallest advantage

in information at its disposal It’s worth pointing out that “greed” isn’t

a pejorative term to an economist A basic founding principle of nomics is that all individuals will naturally maximize their expected

eco-utility subject to a budget constraint Th is is what greed represents here, and it’s not a bad thing But there’s a social aspect to behavior, of course, and greed taken to extremes can have negative moral and ethical impli-cations, even if economists generally don’t think about such things

prices, but in the process, they will quickly eliminate the profi t tunities that motivated their trades in the fi rst place As a result, no prof-its can be garnered from information- based trading, because such profi ts must have already been captured

logic to its counterintuitive conclusion Cardano’s martingale, er’s random walk, Samuelson’s proof, and Fama’s statistics all lead to the

-cient Markets Hypothesis didn’t appear in a vacuum, however It was part of a new quantitative movement in fi nancial economics, along with Harry Markowitz’s optimal portfolio theory; William Sharpe’s Capital Asset Pricing Model (which we’ll come back to in chapter 8); and Fischer Black, Myron Scholes, and Robert C Merton’s option pricing formula

illuminated aspects of market behavior that had remained rious for centuries Of all the discoveries in the new quantitative

crown jewel

thought about fi nancial markets, but they also made these markets

Hy-pothesis gave the investor a democratic alternative to following the cult

of the investment guru Instead of having your stocks handpicked by an adviser who was unlikely to beat the market anyway, you could invest

in passive, low- cost, broadly diversifi ed mutual funds With a little care, you could still beat the hotshot of the week And if your fi nancial cir-cumstances or your tolerance for risk changed, you could rebalance your portfolio, using the new academic theories that described how fi -nancial risk and reward worked— or you could use a new type of invest-ment adviser, an expert steeped in those theories

responsible for the emergence of the index mutual fund business, now a