More Than You Know
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Beware of Behavioral Finance
Misuse of Behavioral Finance Can Lead to Bad Thinking
Optimization by individual agents, often used to derive competitive equilibria, are unnecessary for an actual economy to approximately attain such equilibria. From the failure of humans to optimize in complex tasks, one need not conclude that the equilibria derived from the competitive model are descriptively irrelevant. We show that even in complex economic systems, such equilibria can be attained under a range of surprisingly weak assumptions about agent behavior.
—Antoni Bosch-Domènech and Shyam Sunder, “Tracking the Invisible Hand”
How could economics not be behavioral? If it isn’t behavioral, what the hell is it?
—Charlie Munger, Psychology of Misjudgment
Sorry Syllogism
Classical economic theory assumes that all people have the same preferences, perfect knowledge of all alternatives, and an understanding of the consequences of their decisions. In short, people behave rationally. No one really believes that this idyllic state exists. In fact, ample empirical research and anecdotal evidence show that people are not perfectly rational. This gap between theory and practice has spawned the relatively new field of behavioral finance.1 Behavioral-finance researchers seek to bridge the gap between classical economics and psychology to explain how and why people, and markets, do what they do.
Behavioral finance raises a couple of important issues for investors. The first is whether it is possible to systematically exploit irrational market behavior when it occurs. Another issue is how to avoid making suboptimal decisions as an investor. The goal is to close the gap between how we actually make decisions and how we should make decisions.2
Behavioral finance is undoubtedly important for an intelligent investor. But poor thinking sometimes sneaks under the behavioral finance umbrella—even by the field’s experts. Misusing behavioral-finance concepts can be as problematic as failing to acknowledge the role of psychology in investing.
What’s the issue? We can express the essence of the poor-thinking problem with the following syllogism:Humans are irrational
Markets are made up of humans
Markets are irrational
This logic stream appears to generate one of behavioral finance’s main conclusions. Hersh Shefrin, a leading behavioral-finance researcher, writes: “Behavioral finance assumes that heuristic-driven bias and framing effects cause market prices to deviate from fundamental values.”3 The simple (and somewhat intuitive) message is that the aggregation of irrational individuals must lead to an irrational market.
To see the weakness in this case, we have to consider investor behavior on two levels: collective and individual. Collective behavior addresses the potentially irrational actions of groups. Individual behavior dwells on the fact that we all consistently fall into psychological traps, including overconfidence, anchoring and adjustment, improper framing, irrational commitment escalation, and the confirmation trap.
Here’s my main point: markets can still be rational when investors are individually irrational.4 Sufficient investor diversity is the essential feature in efficient price formation. Provided the decision rules of investors are diverse—even if they are suboptimal—errors tend to cancel out and markets arrive at appropriate prices. Similarly, if these decision rules lose diversity, markets become fragile and susceptible to inefficiency.
So the issue is not whether individuals are irrational (they are) but whether they are irrational in the same way at the same time. So while understanding individual behavioral pitfalls may improve your own decision making, appreciation of the dynamics of the collective is key to outperforming the market. Behavioral-finance enthusiasts often fail to distinguish between the individual and the collective.
Mug’s Game?
Behavioral-finance experts understand the role of diversity in price formation. As Andrei Shleifer writes in his excellent book Inefficient Markets: An Introduction to Behavioral Finance:The efficient market hypothesis does not live or die by investor rationality. In many scenarios where some investors are not fully rational, markets are still predicted to be efficient. In one commonly discussed case, the irrational investors in the market trade randomly. When there are a large number of such investors, and when their trading strategies are uncorrelated, their trades are likely to cancel each other out. In such a market . . . prices are close to fundamental values.
The issue is that the field views this investor diversity as a special case, not the rule. Shleifer continues: “This argument relies crucially on the lack of correlation in strategies of the irrational investors, and, for that reason, is quite limited.”5
Finally, Shleifer argues that arbitrage—another means to bring prices in line with value—is risky and hence restrained in the real world. To sum up the case: Since investors are irrational and their strategies are rarely uncorrelated, markets are inefficient. Further, arbitrage is insufficient to bring markets back to efficiency. So inefficiency is the rule, and efficiency is the exception. Active portfolio management in a fundamentally inefficient market is a mug’s game.
We suspect that most professionals have the sense that efficiency is the rule and inefficiency is the exception. Indeed, we see diverse individuals generate efficient outcomes in many complex systems. In case after case, the collective outperforms the average individual. A full ecology of investors is generally sufficient to assure that there is no systematic way to beat the market. Diversity is the default assumption, and diversity breakdowns are the notable (and potentially profitable) exceptions.
Bombs Away
An unusual search procedure provides an interesting example of the power of the collective. On January 17, 1966, a B-52 bomber and a refueling airplane collided in midair while crossing the Spanish coastline. The bomber carried four nuclear bombs, three of which landed on shore and were immediately found. The fourth bomb, however, was lost in the Mediterranean, and its rapid recovery was essential to U.S. national security.
Assistant Secretary of Defense Jack Howard called a young naval officer, John Craven, to find the bomb. Craven assembled a diverse group of experts and asked them to place Las Vegas-style bets on where the bomb landed. Craven ran their approaches and scenarios through the bet-generated probabilities and found the bomb shortly thereafter. No individual expert had the answer, but the combination of all the experts did.6
Diversity is also a fundamental feature in the problem-solving capabilities of social insects such as ants and bees, including how they acquire food and find new nests. A number of simple illustrations prove the point for human systems as well, including Jack Treynor’s famous jellybean jar experiment. Treynor fills a jar with jellybeans and asks his finance students to guess the total in the jar. He consistently finds that the average guess is both a good estimate of the actual number and better than almost all individual guesses.7
Given what we know about suboptimal human behavior, the critical question is whether investors are sufficiently diverse to generate efficiency. If you think across multiple dimensions, including information sources, investment approach (technical versus fundamental), investment style (value versus growth), and time horizon (short versus long term), you can see why diversity is generally sufficient for the stock market to function well.
Money See, Money Do
Just as diversity tends to yield an efficient market, a diversity breakdown makes markets susceptible to inefficiency. More directly, the collective level is the right place to search for investment opportunities within behavioral finance.8
Herding is a good example. Herding is when many investors make the same choice based on the observations of others, independent of their own knowledge.9 Markets do tend to have phases when one sentiment becomes dominant. These diversity breakdowns are consistent with booms (everyone acts bullish) and busts (everyone acts bearish).
To the best of my knowledge, there is no one barometer that accurately and consistently measures
investor diversity. An objective assessment of public (media) and private opinion probably gives some good clues. The key to successful contrarian investing is to focus on the folly of the many, not the few.
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Raising Keynes
Long-Term Expectations, the El Farol Bar, and Kidding Yourself
The social object of skilled investment should be to defeat the dark forces of time and ignorance which envelop our future. The actual, private object of the most skilled investment today is “to beat the gun”, as Americans so well express it, to outwit the crowd, and to pass the bad, or depreciating, half-crown to the other fellow.
—John Maynard Keynes, The General Theory of Employment
What Do You Expect?
Mark Twain defined a classic as something everyone wants to have read and nobody wants to read. One classic that deserves the attention of all investors is John Maynard Keynes’s General Theory of Employment, and more specifically chapter 12, “The State of Long-Term Expectation.” Expectations are embedded in all the decisions we make, especially investment decisions, but we rarely step back and consider how and why we form our expectations. Keynes guides this reflection.
Let’s take a deeper look at two facets of expectations. The first distinguishes expectations built on deductive processes from those based on inductive processes: deductive processes move from general premises to specific conclusions; inductive processes go from specific facts to general principles.
Deductive rationality, a building block of neoclassical economics, breaks down in the real world because human logical reasoning can’t handle situations that are too complicated (i.e., we have bounded rationality), and any action that deviates from rationality in human interactions ignites speculation about how others will behave.1 In other words, if no one else is rational, it doesn’t pay for you to be.
The second facet of expectations is that after an event occurs, humans tend to overestimate their pre-event knowledge of the outcome. This hindsight bias erodes the quality of the feedback we need to sharpen our analytical skills.
Speculation and Enterprise
Keynes divides the basis for expectations of future returns (he uses the word “yield”) into two parts: facts that are more or less certain, and events that you can forecast with varying degrees of confidence. These latter, uncertain events include the magnitude and type of investment, as well as demand fluctuations. He calls the psychological expectations for these events the “state of long-term expectation.”
In forming forecasts, most people fall back on what Keynes calls a “convention”—they start with the current situation and modify it when they have definite reasons to expect a change.2 He notes that the magnitude of the modification reflects “the state of confidence,” a combination of actual market observations and business psychology. But there is no way to anticipate what the state of confidence will be because it relies on feedback. Markets affect psychology and psychology affects markets.3
Keynes argues that conventions are inherently precarious for a host of reasons. The most famous of these is that many investors focus not on “enterprise”—forecasting long-term return on investments—but rather on “speculation”—forecasting the market’s psychology. Here, he invokes his most famous metaphor: markets as a beauty contest. The goal is not to identify the person you find the most beautiful, or even the person you think the average beholder finds most beautiful. You soon find yourself trying to decipher what the average opinion thinks the average opinion is. Through the beauty contest metaphor, Keynes describes the limitations of a deductive approach to economics and markets.
This is not to say, though, that Keynes perceives markets to run solely on emotion. In his words,The state of long-term expectation is often steady, and, even when it is not, the other factors exert their compensating effects. We are merely reminding ourselves that human decisions affecting the future, whether personal or political or economic, cannot depend on strict mathematical expectation, since the basis for making such calculations does not exist.4
In what is a timeless observation, Keynes adds, “Speculators may do no harm as bubbles on a steady stream of enterprise. But the position is serious when enterprise becomes the bubble on a whirlpool of speculation.”5
Are today’s institutional investors more focused on enterprise or speculation? This is a difficult question to answer, and markets certainly need an ecology of investors to remain robust. But the aggregate statistics on equity portfolio turnover give any intelligent investor pause. Annual turnover has shot from roughly 30 to 40 percent in the early 1970s to about 90 percent today. This means the average holding period for a stock is now just over one year. Not only is this turnover costly, it has also attended a disquieting decline in corporate governance.6
Visiting El Farol
Economist Brian Arthur has made important contributions to our understanding of inductive versus deductive approaches to problem solving (including stock picking). Arthur notes that you can solve only the easiest problems deductively: you can do it for tic-tac-toe but not for chess. Indeed, experiments show that humans aren’t that good at deductive logic. But humans are superb at recognizing and matching patterns. We’re inductive machines.
Arthur offers a model of inductive reasoning, effectively picking up where Lord Keynes left off. The model is based on the El Farol bar in Santa Fe, New Mexico, which played Irish music on Thursday nights.7 Attending the El Farol when it isn’t too crowded is fun; you can enjoy your pint and the band without being disturbed. But the bar is a turn-off when it is packed—the jostling crowd spills your beer and the loud voices drown out the band. So how do you decide whether or not you should go to El Farol?
To make the problem more concrete, Arthur suggests that the bar has a hundred-person capacity and that with sixty people or fewer it is not crowded and with more than sixty it is. So an individual expecting that less than sixty people will be there will go, while one expecting more than sixty will stay home. The decision to go is independent of past choices, the patrons don’t talk or coordinate, and the only basis for making a decision is past attendance.
This problem has two notable features. First, the problem is too complicated for a deductive solution. As individuals can only look at past attendance, there are a large number of legitimate expectational models. The potential bar goers must use an inductive approach. Second, common expectations backfire. If all believe most will go, nobody will go. And if all believe nobody will go, all will go. Like Keynes’s beauty contest, the issue is not just what you believe but rather what you believe others to believe.
Researchers have constructed models of the El Farol problem by assigning individuals evolving decision rules. With sufficient rule diversity and enough iterations, the mean attendance for the bar approximates the overcrowding threshold of sixty. One study assumed 20,000 iterations, which is about 385 years worth of Thursday nights.8 This means that even inductive approaches may generate results similar to deductive methods, provided there is sufficient strategy diversity.
Keynes and Arthur both draw out a fundamental truth about markets: many investment choices are not, and cannot be, based on mathematical, deductive methods. I would add that, on the whole, a full ecology of strategies is sufficient to generate efficient markets. But when diversity is jeopardized—which it frequently is—markets depart significantly from the underlying fundamentals.
Kidding Yourself
A discussion of expectation is not complete without noting an odd human feature: once an event has passed, we tend to believe that we had better knowledge of the outcome before the fact than we really did. Known as hindsight bias, or more commonly the Monday-morning-quarterback syndrome, this research shows that people are not very good at recalling the way an uncertain situation appeared to them before finding out the results.9
Finance professor Hersh Shefrin illustrates the point by analyzing the comments of a former Orange County treasurer, Robert Citron.10 In his annual report dated September
1993, Citron wrote, “We will have level if not lower interest rates through this decade. Certainly, there’s nothing in the horizon that would indicate that we will have rising interest rates for a minimum of three years.” In February 1994, the Federal Reserve Board raised rates. Citron’s response: “The recent increase in rates was not a surprise to us; we expected it and were prepared for it.” Now, there is a chance that Citron changed his view prior to the rate hike. But the much more plausible view is that he suffered from hindsight bias.
Hindsight bias stands in the way of quality feedback—understanding how and why we made a particular decision. One antidote to this bias is to keep notes of why you make decisions as you make them. Those notes become a valuable source of objective feedback and can help sharpen future decision making.
16
Right from the Gut
Investing with Naturalistic Decision Making
People who make decisions for a living are coming to realize that in complex or chaotic situations—a battlefield, a trading floor, or today’s brutally competitive business environment—intuition usually beats rational analysis. And as science looks closer, it is coming to see that intuition is not a gift but a skill.