Chapter 17

The Theory Police

Investors must expect to lose occasionally on the risks they take. Any other assumption would be foolish. But theory predicts that the expectations of rational investors will be unbiased, to use the technical expression: a rational investor will overestimate part of the time and underestimate part of the time but will not overestimate or underestimate all of the time—or even most of the time. Rational investors are not among the people who always see the glass as either half empty or half full.

Nobody really believes that the real-life facts fit that stylized description of investors always rationally trading off risk and return. Uncertainty is scary. Hard as we try to behave rationally, our emotions often push us to seek shelter from unpleasant surprises. We resort to all sorts of tricks and dodges that lead us to violate the rational prescriptions. As Daniel Kahneman points out, “The failure of the rational model is not in its logic but in the human brain it requires. Who could design a brain that could perform the way this model mandates? Every single one of us would have to know and understand everything, completely and at once.”1 Kahneman was not the first to recognize the rigid constraints of the rational model, but he was one of the first to explain the consequences of that rigidity and the manner in which perfectly normal human beings regularly violate it.

If investors have a tendency to violate the rational model, that model may not be a very reliable description of how the capital markets behave. In that case, new measures of investment risk would be in order.

Consider the following scenario. Last week, after weeks of indecision, you finally liquidated your long-standing IBM position at $80 share. This morning you check your paper and discover that IBM is selling at $90. The stock you bought to replace IBM is down a little. How do you react to this disappointing news?

Your first thought might be whether you should tell your spouse about what has happened. Or you might curse yourself for being impatient. You will surely resolve to move more slowly in the future before scrapping a long-term investment, no matter how good an idea it seems. You might even wish that IBM had disappeared from the market the instant you sold it, so that you would never learn how it performed afterward.

The psychologist David Bell has suggested that “decision regret” is the result of focusing on the assets you might have had if you had made the right decision.2 Bell poses the choice between a lottery that pays $10,000 if you win and nothing if you lose versus $4,000 for certain. If you choose to play the lottery and lose, you tell yourself that you were greedy and were punished by fate, but then you go on about your business. But suppose you choose the $4,000 certain, the more conservative choice, and then find out that the lottery paid off at $10,000. How much would you pay never to learn the outcome?

Decision regret is not limited to the situation in which you sell a stock and then watch it go through the roof. What about all those stocks you never bought, many of which are performing better than the stocks you did buy? Even though everyone knows it is impossible to choose only top performers, many investors suffer decision regret over those forgone assets. I believe that this kind of emotional insecurity has a lot more to do with decisions to diversify than all of Harry Markowitz’s most elegant intellectual perorations on the subject—the more stocks you own, the greater the chance of holding the big winners!

A similar motivation prompts investors to turn their trading over to active portfolio managers, despite evidence that most of them fail to outperform the major market indexes over the long run. The few who do succeed on occasion tend to show little consistency from year to year; we have already seen how difficult it was to distinguish between luck and skill in the cases of American Mutual and AIM Constellation.a Yet the law of averages predicts that about half the active managers will beat the market this year. Shouldn’t your manager be among them? Somebody is going to win out, after all.

The temptations generated by thoughts of forgone assets are irresistible to some people. Take Barbara Kenworthy, who was manager of a $600 million bond portfolio at Prudential Investment Advisors in May 1995. The Wall Street Journal quoted Ms. Kenworthy as saying, “We’re all creatures of what burned us most recently.”3 To explain what she meant, the Journal commented, “Ms. Kenworthy is plunging into long-term bonds again despite her reckoning that value isn’t quite there, because not to invest would be to momentarily lag behind the pack.” The reporter, with a sense of the ironic, then remarked, “This is an intriguing time horizon for an investor in 30-year bonds.”

Imagine yourself as an investment adviser trying to decide whether to recommend Johnson & Johnson or a start-up biogenetic company to a client. If all goes well, the prospects for the start-up company are dazzling; Johnson & Johnson, though a lot less exciting, is a good value at its current price. And Johnson & Johnson is also a “fine” company with a widely respected management team. What will you do if you make the wrong choice? The day after you recommend the start-up company, its most promising new drug turns out to be a wash-out. Or right after you recommend Johnson & Johnson, another pharmaceutical company issues a new product to compete with its biggest-selling drug. Which outcome will generate less decision regret and make it easier to go on working with a disgruntled client?

Keynes anticipated this question in The General Theory. After describing an investor with the courage to be “eccentric, unconventional and rash in the eyes of average opinion,” Keynes says that his success “will only confirm the general belief in his rashness; and . . . if his decisions are unsuccessful. . . he will not receive much mercy. Worldly wisdom teaches that it is better for reputation to fail conventionally than to succeed unconventionally.”4

Prospect Theory confirms Keynes’s conclusion by predicting which decision you will make. First, the absolute performance of the stock you select is relatively unimportant. The start-up company’s performance as compared with Johnson & Johnson’s performance taken as a reference point is what matters. Second, loss aversion and anxiety will make the joy of winning on the start-up company less than the pain if you lose on it. Johnson & Johnson is an acceptable “long-term” holding even if it often underperforms.

The stocks of good companies are not necessarily good stocks, but you can make life easier by agreeing with your clients that they are. So you advise your client to buy Johnson & Johnson.

I am not making up a story out of whole cloth. An article in The Wall Street Journal of August 24, 1995, goes on at length about how professional investment managers have grown leery of investing in financial instruments known as derivatives—the subject of the next chapter—as a result of the widely publicized disasters at Procter & Gamble and in Orange County, California, among others. The article quotes John Carroll, manager of GTE Corporation’s $12 billion pension fund: “If you made the right call and used derivatives, you might get a small additional return. But if you make the wrong call, you could wind up unemployed, with a big dent in your credibility as an investor.” Andrew Turner, director of research at a leading consulting firm for institutional investors, adds, “Even if you keep your job, you don’t want to get labeled as [someone] who got snookered by an investment bank.” A major Boston money manager agrees: “If you buy comfortable-looking . . . stocks like Coca Cola, you’re taking very little career risk because clients will blame a stupid market if things go wrong.”

With Richard Thaler in the vanguard, a group of academic economists have responded to flaws in the rational model by launching a new field of study called “behavioral finance.” Behavioral finance analyzes how investors struggle to find their way through the give and take between risk and return, one moment engaging in cool calculation and the next yielding to emotional impulses. The result of this mixture between the rational and not-so-rational is a capital market that itself fails to perform consistently in the way that the theoretical models predict that it will perform.

Meir Statman, a professor in his late forties at the University of Santa Clara, describes behavioral finance as “not a branch of standard finance: it is its replacement with a better model of humanity.”5 We might dub the members of this group the Theory Police, because they are constantly checking to see whether investors are obeying or disobeying the laws of rational behavior as laid down by the Bernoullis, Jevons, von Neumann, Morgenstern, and Markowitz.

Richard Thaler started thinking about these problems in the early 1970s, while working on his doctoral dissertation at the University of Rochester, an institution known for its emphasis on rational theory.6 His subject was the value of a human life, and he was trying to prove that the correct measure of that value is the amount people would be willing to pay to save a life. After studying risky occupations like mining and logging, he decided to take a break from the demanding statistical modeling he was doing and began to ask people what value they would put on their own lives.

He started by asking two questions. First, how much would you be willing to pay to eliminate a one-in-a-thousand chance of immediate death? And how much would you have to be paid to accept a one-in-a-thousand chance of immediate death? He reports that “the differences between the answers to the two questions were astonishing. A typical answer was ‘I wouldn’t pay more than $200, but I wouldn’t accept an extra risk for $50,000!’” Thaler concluded that “the disparity between buying and selling prices was very interesting.”

He then decided to make a list of what he called “anomalous behaviors”—behaviors that violated the predictions of standard rational theory. The list included examples of large differences between the prices at which a person would be willing to buy and sell the same item. It also included examples of the failure to recognize sunk costs—money spent that would never be recouped—as with the $40 theater ticket in the previous chapter. Many of the people he questioned would “choose not to choose regret.” In 1976, he used the list as the basis for an informal paper that he circulated only to close friends and “to colleagues I wanted to annoy.”

Shortly thereafter, while attending a conference on risk, Thaler met two young researchers who had been converted by Kahneman and Tversky to the idea that so-called anomalous behavior is often really normal behavior, and that adherence to the rules of rational behavior is the exception. One of them later sent Thaler a paper by Kahneman and Tversky called “Judgment Under Uncertainty.” After reading it, Thaler remarks, “I could hardly contain myself.”7 A year later, he met Kahneman and Tversky and he was off and running.

Meir Statman began to be interested in nonrational behavior when, as a student of economics, he noted that people reveal a tendency to look at problems in pieces rather than in the aggregate. Even qualified scholars in reputable journals reached faulty conclusions by failing to recognize that the whole is the product of interaction among its parts, or what Markowitz called covariances, rather than just a collection of discrete pieces. Statman soon recognized that the distortions caused by mental accounting were by no means limited to the public at large.

Statman cites a case that he found in a journal about a homeowner’s choice between a fixed-rate mortgage and a variable-rate mortgage.8 The paper dealt with the covariance between mortgage payments and the borrower’s income and concluded that variable rates were appropriate for people whose income generally keeps pace with inflation and that fixed rates were appropriate for people whose incomes is relatively constant. But Statman noted that the authors ignored the covariance between the value of the house itself and the two variables mentioned; for example, an inflationary rise in the value of the house might make a variable-rate mortgage easy enough to carry regardless of what happened to the homeowner’s income.

In 1981, Hersh Shefrin, a colleague of Statman’s at Santa Clara University, showed Statman a paper titled “An Economic Theory of Self-Control,” which Shefrin had written with Thaler.9 The paper made the point that people who have trouble exercising self-control deliberately limit their options. People with weight problems, for example, avoid having a cake ready at hand. The paper also noted that people choose to ignore the positive covariance between their mortgage payments and the value of their house as borrowing collateral; they view the house as a “piggy bank” that is not to be touched, even though they always have the option to borrow more against it and, thanks to home equity loans, sometimes do.b The paper made the point that people who have trouble exercising self-control deliberately limit their options. People with weight problems, for example, avoid having a cake ready at hand. The paper also noted that people choose to ignore the positive covariance between their mortgage payments and the value of their house as borrowing collateral; they view the house as a “piggy bank” that is not to be touched, even though they always have the option to borrow more against it and, thanks to home equity loans, sometimes do.b After reading this paper, Statman too was off and running.

A year later, Shefrin and Statman collaborated on an illuminating paper on behavioral finance titled “Explaining Investor Preference for Cash Dividends,”10 which appeared in the Journal of Financial Economics in 1984.

Why corporations pay dividends has puzzled economists for a long time. Why do they pay out their assets to stockholders, especially when they themselves are borrowing money at the same time? From 1959 to 1994, nonfinancial corporations in the United States borrowed more than $2 trillion while paying out dividends of $1.8 trillion.c They could have avoided nearly 90% of the increase in their indebtedness if they had paid no dividends at all.

From 1959 to 1994, individuals received $2.2 trillion of the dividends distributed by all corporations, financial as well as nonfinancial, and incurred an income-tax liability on every dollar of that money. If corporations had used that money to repurchase outstanding shares in the open market instead of distributing it in dividends, earnings per share would have been larger, the number of outstanding shares would have been smaller, and the price of the shares would have been higher. The remaining stockholders could have enjoyed “home-made” dividends by selling off their appreciated shares to finance their consumption and would have paid the lower tax rate on capital gains that prevailed during most of that period. On balance, stockholders would have been wealthier than they had been.

To explain the puzzle, Shefrin and Statman draw on mental accounting, self-control, decision regret, and loss aversion. In the spirit of Adam Smith’s “impartial spectactor” and Sigmund Freud’s “superego,” investors resort to these deviations from rational decision-making because they believe that limiting their spending on consumption to the amount of income they receive in the form of dividends is the way to go; financing consumption by selling shares is a no-no.

Shefrin and Statman hypothesize the existence of a split in the human psyche. One side of our personality is an internal planner with a long-term perspective, an authority who insists on decisions that weight the future more heavily than the present. The other side seeks immediate gratification. These two sides are in constant conflict.

The planner can occasionally win the day just by emphasizing the rewards of self-denial. But when the need arises, the planner can always talk about dividends. As the light fixture “hides” the liquor bottle from the alcoholic, dividends “hide” the pool of capital that is available to finance immediate gratification. By repeatedly reciting the lesson that spending dividends is acceptable but that invading principal is sinful, the planner keeps a lid on how much is spent on consumption.

Once that lesson is driven home, however, investors become insistent that the stocks they own pay a reliable dividend and hold out a promise of regular increases. No dividend, no money to spend. No choice. Selling a few shares of stock and the receipt of a dividend are perfect substitutes for financing consumption in theory—and selling shares even costs less in taxes—but in a setting of self-control contrivances, they are far from perfect substitutes in practice.

Shefrin and Statman ask the reader to consider two cases. First, you take $600 of dividend income and buy a television set. Second, you sell $600 of stock and use the proceeds to buy a television set. The following week, the company becomes a takeover candidate and the stock zooms. Which case causes you more regret? In theory, you should be indifferent. You could have used the $600 of dividend income to buy more shares of the stock instead of buying the TV. So that was just as costly a decision as your decision to sell the shares to finance the TV. Either way, you are out the appreciation on $600 worth of shares.

But oh, what a horror if dividends are cut! In 1974, when the quadrupling of oil prices forced Consolidated Edison to eliminate its dividend after 89 years of uninterrupted payments, hysteria broke out at the company’s annual meeting of stockholders. Typical was one question put to the company chairman, “What are we to do? You don’t know when the dividend is coming back. Who is going to pay my rent? I had a husband. Now Con Ed has to be my husband.” This shareholder never gave a thought to the possibility that paying dividends out of losses would only weaken the company and might ultimately force it into bankruptcy. What kind of a husband would that be? Selling her shares to pay the rent was not one of the options she allowed herself to consider; the dividend income and the capital were kept in separate pockets as far as she was concerned. As in a good marriage, divorce was inadmissible.

In a discussion of Shefrin and Statman’s work, Merton Miller, a Nobel Laureate at the University of Chicago and one of the more formidable defenders of rational theory, made the following observation about investors who do not rely on professional advisers:

For these investors, stocks are usually more than just the abstract “bundles of returns” of our economic models. Behind each holding may be a story of family business, family quarrels, legacies received, [and] divorce settlements . . . almost totally irrelevant to our theories of portfolio selection. That we abstract from all these stories in building our models is not because the stories are uninteresting but because they may be too interesting and thereby distract us from the pervasive market forces that should be our principal concern.11

In Chapter 10, I mentioned a paper titled “Does the Stock Market Overreact?” which Thaler and one of his graduate students, Werner DeBondt, presented at the annual meeting of the American Finance Association in December 1985. There this paper served as an example of regression to the mean. It can also serve as an example of the failure of the theory of rational behavior.

I was a discussant at the session at which Thaler and DeBondt presented their findings, and I began by saying, “At long last, the academic world has caught up with what investors have known all along.”12 Their answer to the question posed by the title was an unqualified “Yes.”

As an example of Prospect Theory, Thaler and DeBondt demonstrated that, when new information arrives, investors revise their beliefs, not according to the objective methods set forth by Bayes, but by overweighting the new information and underweighting prior and longer-term information. That is, they weight the probabilities of outcomes on the “distribution of impressions” rather than on an objective calculation based on historical probability distributions. As a consequence, stock prices systematically overshoot so far in either direction that their reversal is predictable regardless of what happens to earnings or dividends or any other objective factor.

The paper provoked criticism from members of the audience who were shocked by this evidence of irrational pricing. The dispute continued over a number of years, focusing primarily on the manner in which Thaler and DeBondt had gathered and tested their data. One problem related to the calendar: an excessive proportion of the profits from selling the winners and buying the losers appeared in the one month of January; the rest of the year appeared to have been about break-even. But different tests by different folks continued to produce conflicting results.

In May 1993, a related paper entitled “Contrarian Investment, Extrapolation, and Risk” appeared under the auspices of the prestigious National Bureau of Economic Research.13 The three academic authors, Josef Lakonishok, André Shleifer, and Robert Vishny, provided an elaborate statistical analysis which confirmed that so-called “value” stocks—stocks that sell at low prices relative to company earnings, dividends, or assets—tend to outperform more highly valued stocks even after adjustments for volatility and other accepted measures of risk.

The paper was memorable for more than the conclusion it reached, which was not original by any means, nor for the thoroughness and polish of the statistical presentation. Its importance lay in its confirmation of Thaler and DeBondt’s behavioral explanation of these kinds of results. In part because of fear of decision regret and in part because of myopia, investors price the stocks of troubled companies too low in the short run when regression to the mean would be likely to restore most of them to good health over the long run. By the same token, companies about which recent information has indicated sharp improvement are overpriced by investors who fail to recognize that matters cannot get better and better indefinitely.

Lakonishok, Shleifer, and Vishny have certainly convinced themselves. In 1995, they launched their own firm to manage money in accordance with their contrarian model.

Thaler never recovered from his early fascination with that “very interesting” disparity between prices for which people were willing to buy and sell the identical items. He coined the expression “endowment effect” to describe our tendency to set a higher selling price on what we own (are endowed with) than what we would pay for the identical item if we did not own it.d

In a paper written in 1990 with Daniel Kahneman and another colleague, Jack Knetsch, Thaler reported on a series of classroom experiments designed to test the prevalence of the endowment effect.14 In one experiment, some of the students were given Cornell coffee mugs and were told they could take them home; they were also shown a range of prices and asked to set the lowest price at which they would consider selling their mug. Other students were asked the highest price they would be willing to pay to buy a mug. The average owner would not sell below $5.25, while the average buyer would not pay more than $2.25. A series of additional experiments provided consistent results.

The endowment effect is a powerful influence on investment decisions. Standard theory predicts that, since rational investors would all agree on investment values, they would all hold identical portfolios of risky assets like stocks. If that portfolio proved too risky for one of the investors, he could combine it with cash, while an investor seeking greater risk could use the portfolio as collateral for borrowings to buy more of the same.

The real world is not like that at all. True, the leading institutional investors do hold many stocks in common because the sheer volume of dollars they must invest limits them to stocks with the highest market values—stocks like General Electric and Exxon. But smaller investors have a much wider range of choice. It is rare indeed to find two of them holding identical portfolios, or even to find significant duplication in holdings. Once something is owned, its owner does not part with it lightly, regardless of what an objective valuation might reveal.

For example, the endowment effect arising from the nationality of the issuing company is a powerful influence on valuation. Even though international diversification of investment portfolios has increased in recent years, Americans still hold mostly shares of American companies and Japanese investors hold mostly shares of Japanese companies. Yet, at this writing, the American stock market is equal to only 35% and the Japanese to only 30% of the world market.

One explanation for this tendency is that it is more costly to obtain information on securities in a foreign market than it is to obtain information on securities in the home market. But that explanation seems insufficient to explain “such a great difference in holdings. There must be more compelling reasons why investors are so reluctant to hold securities domiciled in markets that account for 65% to 70% of the investible universe.

A masterful study of the influence of the endowment effect on international investing was carried out in 1989 by Kenneth French, then at the University of Chicago and now at Yale, and James Poterba at MIT.15 The target of their inquiry was the absence of cross-border ownership between Japanese and American investors. At that time, Japanese investors owned just over 1% of the U.S. stock market, while American investors owned less than 1% of the Tokyo market. A good deal of activity was taking place across the borders; substantial buying and selling of American stocks went on in Japan and of Japanese stocks in the United States. But net purchases on either side were tiny.

The result was a striking distortion of valuations across the markets. French and Poterba’s calculations indicated that the small holdings of Japanese stocks by U.S. investors could be justified only if the Americans expected annual real (inflation-adjusted) returns of 8.5% in the United States and 5.1% in Japan. The small holdings of American stocks by Japanese investors could be justified only if the Japanese expected real annual returns of 8.2% in Japan and 3.9% in the United States. Neither taxation nor institutional restrictions were sufficient to explain disparities that would set von Neumann spinning in his grave.e Nor could theories of rational investor decision-making explain them. The endowment effect must be the answer.f

The evidence presented in this chapter gives only a hint of the diligence of the Theory Police in apprehending people in the act of violating the precepts of rational behavior. The literature on that activity is large, growing, and diverse.

Now we come to the greatest anomaly of all. Even though millions of investors would readily plead guilty to acting in defiance of rationality, the market—where it really counts—act as though rationality prevailed.

What does it mean to say “where it really counts”? And, if that is the case, what are the consequences for managing risk?

Keynes provides a precise definition of what it means to say “where it really counts.” In a famous passage in The General Theory of Employment, Interest and Money, Keynes describes the stock market as, “. . . so to speak, a game of Snap, of Old Maid, of Musical Chairs—a pastime in which he is victor who says Snap neither too soon nor too late, who passes the Old Maid to his neighbor before the game is over, who secures a chair for himself when the music stops.”16

Keynes’s metaphor suggests a test to determine whether the market acts as though rationality prevails, where it counts: the prevalence of nonrational behavior should provide endless opportunities for rational investors to say Snap, to pass on the Old Maid, or to seize a chair ahead of investors on the run from the Theory Police. If those opportunities do not present themselves, or are too brief to provide an advantage, we might just as well assume that the market is rational even though we recognize that many irrational forces are coursing through it. “Where it counts” means that there are very few opportunities to profit by betting against irrational investors, even though there is so much evidence of their presence in the market. Where it counts, the market’s behavior conforms to the rational model.

If all investors went through the identical rational thinking process, expected returns and adjustments for risk would look the same to everyone in possession of the same information at the same moment. In the unlikely event that a few investors succumbed to nonrational behavior, they would end up buying high and selling low as better-informed investors were driving prices back to a rational valuation. Otherwise, prices would change only when new information became available, and new information arrives in random fashion.

That is how a fully rational market would work. No one could outperform the market as a whole. All opportunities would be exploited. At any level of risk, air investors would earn the same rate of return.

In the real world, investors seem to have great difficulty outperforming one another in any convincing or consistent fashion. Today’s hero is often tomorrow’s blockhead. Over the long run, active investment managers—investors who purport to be stock-pickers and whose portfolios differ in composition from the market as a whole—seem to lag behind market indexes like the S&P 500 or even broader indexes like the Wilshire 5000 or the Russell 3000. Over the past decade, for example, 78% of all actively managed equity funds underperformed the Vanguard Index 500 mutual fund, which tracks the unmanaged S&P 500 Composite; the data for earlier periods are not as clean, but the S&P has been a consistent winner over long periods of time.

There is nothing new about this pattern. In 1933, Alfred Cowles, a wealthy investor and a brilliant amateur scholar, published a study covering a large number of printed financial services as well as every purchase and sale made over four years by twenty leading fire insurance companies. Cowles concluded that the best of a series of random forecasts made by drawing cards from an appropriate deck was just as good as the best of a series of actual forecasts, and that the results achieved by the insurance companies “could have been achieved through a purely random selection of stocks.”17 Today, with large, sophisticated, and well-informed institutional investors dominating market activity, getting ahead of the market and staying there is far more difficult than it was in the past.

If investors are unable to outguess one another with any degree of reliability, perhaps the computer can capitalize on the market’s nonrational behavior; machines are immune from such human flaws as the endowment effect, myopia, and decision regret. So far, computer models that instruct the investor to buy when others are frightened and to sell when others are overconfident have produced mixed or irregular results. The investors become either more frightened or more overconfident than the computer model predicts, or else their behavior is outside the patterns the computer can recognize. Yet computerized trading is a fruitful area for further research, as we shall see shortly.

Human investors do turn in outstanding track records from time to time. But even if we ascribe those achievements to skill rather than luck, two problems remain.

First, past performance is a frail guide to the future. In retrospect, the winners are fully visible, but we have no reliable way of identifying in advance the investors whose skills will win out in the years ahead. Timing also matters. Even the most successful investors, people like Benjamin Graham and Warren Buffett, have had long periods of under-performance that would make any manager wince. Others zoom to fame on one or two brilliant calls, only to fall flat when their public following grows large. No one knows when their next takeoff will come, if ever.

The fine performance record of unmanaged index funds is vulnerable to the same kinds of criticism, because the guidance provided by past performance is no more reliable here than it is for active managements. Indeed, more dramatically than any other portfolio, the indexes reflect all the fads and nonrational behavior that is going on in the market. Yet a portfolio designed to track one of the major indexes, like the S&P 500, still has clear advantages over actively managed portfolios. Since turnover occurs only when a change is made in the index, transaction costs and capital-gains taxes can be held to a minimum. Furthermore, the fees charged by managers of index funds run about 0.10% of assets; active managers charge many times that, often exceeding 1% of assets. These built-in advantages are due neither to luck nor are they sensitive to some particular time period; they are working for the investor all the time.

The second problem in relying on evidence of superior management skills is that winning strategies tend to have a brief half-life. Capital markets as active and liquid as ours are so intensely competitive that results from testing ideas on past data are difficult to replicate or sustain in real time. Many smart people fail to get rich because people not so smart soon follow in their footsteps and smother the advantage their strategy was designed to create.

Because of the danger that free-riders will hop aboard a successful strategy, it is quite possible that there are investors out there who beat the market consistently beyond the probability of luck but who stubbornly guard their obscurity. Nobel Laureate Paul Samuelson, an eloquent defender of the hypothesis that markets act as though they were rational, has admitted that possibility: “People differ in their heights, pulchritude, and acidity, why not in their P.Q., or performance quotient?” But he goes on to point out that the few people who have high P.Q.s are unlikely to rent their talents “to the Ford Foundation or the local bank trust department. They have too high an I.Q. for that.”18 You will not find them on Wall Street Week, on the cover of Time, or contributing papers to scholarly journals on portfolio theory.

Instead, they are managing private partnerships that limit the number of investors they accept and that mandate seven-figure minimum participations. Since they participate in the capital appreciation as well as receiving a fee, adding other people’s money to their own gives them an opportunity to leverage their P.Q.s. It may well be that some of them would qualify as Snap champs.

In Chapter 19 we shall look at what some of these investors are trying to do. Their strategies draw on theoretical and empirical concepts that reach back to the origins of probability and to the Chevalier de Méré himself. But those strategies incorporate a more complex view of market rationality than I have set forth. If there is validity to the notion that risk equals opportunity, this little tribe is showing the way.

Nevertheless, private partnerships are peripheral to the mainstream of the marketplace. Most investors either have too little money to participate, or, like the giant pension funds, they are so big that they cannot allocate a significant portion of their assets to the partnerships. Moreover, the funds may be inhibited by the fear of decision regret in the event that these unconventional investments go sour. In any case, when the largest investors begin to experiment with exotic quantitative concepts, they must be careful not to get in each other’s way.

What are the consequences of all this for managing risks? Does the presence of nonrational behavior make investing a riskier activity than it would otherwise be? The answer to that question requires putting it into its historical setting.

Capital markets have always been volatile, because they trade in nothing more than bets on the future, which is full of surprises. Buying shares of stock, which carry no maturity date, is a risky business. The only way investors can liquidate their equity positions is by selling their shares to one another: everyone is at the mercy of everyone else’s expectations and buying power. Similar considerations apply to bonds, which return their principal value in cash to their owners but only at some future date.

Such an environment provides a perfect setting for nonrational behavior: uncertainty is scary. If the nonrational actors in the drama overwhelm the rational actors in numbers and in wealth, asset prices are likely to depart far from equilibrium levels and to remain there for extended periods of time. Those periods are often long enough to exhaust the patience of the most rational of investors. Under most circumstances, therefore, the market is more volatile than it would be if everyone signed up for the rational model and left Kahneman and Tversky to find other fields to plow.19

Nevertheless, explicit attention to investment risk and to the tradeoff between risk and return is a relatively young notion. Harry Markowitz laid out the basic idea for the first time only in 1952, which seems like a long time ago but is really a late-comer in the history of markets. And with a great bull market getting under way in the early 1950s, Markowitz’s focus on the risks of portfolio selection attracted little attention at the time. Academic interest speeded up during the 1960s, but it was only after 1974 that practitioners sat up and took notice.

The explanation for this delayed reaction has to do with changes in the volatility of the market. From 1926 to 1945—a period that included the Great Crash, the Depression, and the Second World War—the standard deviation of annual total returns (income plus change in capital values) was 37% a year while returns averaged only about 7% a year. That was really risky business!

Investors brought that memory bank to the capital markets in the late 1940s and on into the 1950s. Once burned, twice shy. A renewal of speculative fever and unbridled optimism was slow to develop despite a mighty bull market that drove the Dow Jones Industrial Average from less than 200 in 1945 to 1,000 by 1966. From 1946 to 1969, despite a handsome return of over 12% a year and a brief outburst of speculative enthusiasm in 1961, the standard deviation of total returns was only one-third of what it had been from 1926 to 1945.

This was the memory that bank investors carried into the 1970s. Who would worry about risk in a market like that? Actually, everyone should have worried. From the end of 1969 to the end of 1975, the return on the S&P 500 was only half what it had been from 1946 to 1969, while the annual standard deviation nearly doubled, to 22%. During 12 of the 24 calendar quarters over this period, an investor in the stock market would have been better off owning Treasury bills.

Professional managers, who by 1969 had pushed client portfolios as high as 70% in common stocks, felt like fools. Their clients took an even harsher view. In the fall of 1974, the maiden issue of The Journal of Portfolio Management carried a lead article by a senior officer of Wells Fargo Bank who admitted the bitter truth:

Professional investment management and its practitioners are inconsistent, unpredictable, and in trouble. . . . Clients are afraid of us, and what our methods might produce in the way of further loss as much or more than they are afraid of stocks. . . . The business badly needs to replace its cottage industry operating methods.20

For the first time risk management became the biggest game in town. First came a major emphasis on diversification, not only in stock holdings, but across the entire portfolio, ranging from stocks to bonds to cash assets. Diversification also forced investors to look into new areas and to develop appropriate management techniques. The traditional strategy of buy-and-hold-until-maturity for long-term bonds, for example, was replaced by active, computer-based management of fixed-income assets. Pressures for diversification also led investors to look outside the United States. There they found opportunities for high returns, quite apart from the diversification benefits of international investing.

But even as the search for risk-management techniques was gaining popularity, the 1970s and the 1980s gave rise to new uncertainties that had never been encountered by people whose world view had been shaped by the benign experiences of the postwar era. Calamities struck, including the explosion in oil prices, the constitutional crisis caused by Watergate and the Nixon resignation, the hostage-taking in Teheran, and the disaster at Chernobyl. The cognitive dissonances created by these shocks were similar to those experienced by the Victorians and the Edwardians during the First World War.

Along with financial deregulation and a wild inflationary sleighride, the environment generated volatility in interest rates, foreign exchange rates, and commodity prices that would have been unthinkable during the preceding three decades. Conventional forms of risk management were incapable of dealing with a world so new, so unstable, and so frightening.

These conditions gave rise to a perfect example of Ellsberg’s ambiguity aversion. We can calculate probabilities from real-life situations only when similar experiences have occurred often enough to resemble the patterns of games of chance. Going out without an umbrella on a cloudy day is risky, but we have seen enough cloudy days and have listened to enough weather reports to be able to calculate, with some accuracy, the probability of rain. But when events are unique, when the shape and color of the clouds have never been seen before, ambiguity takes over and risk premiums skyrocket. You either stay home or take the umbrella whenever you go out, no matter how inconvenient. That is what happened in the 1970s, when the valuations of both stocks and bonds were extremely depressed compared with the valuations that prevailed during the 1960s.

The alternative is to discover methods to mute the impact of the unexpected, to manage the risk of the unknown. Although diversification has never lost its importance, professional investors recognized some time ago that it was both inadequate as a risk-management technique and too primitive for the new environment of volatility and uncertainty.

Fortuitously perhaps, impressive technological innovation coincided with the urgent demand for novel methods of risk control. Computers were introduced into investment management just as concerns about risk were escalating. Their novelty and extraordinary power added to the sense of alienation, but at the same time computers greatly expanded the capacity to manipulate data and to execute complex strategies.

If, as Prospect Theory suggested, investors had met the enemy and it was them, now the search was on for protective measures that made more sense than decision regret or myopia or the endowment effect. A new age of risk management was about to open, with concepts, techniques, and methodologies that made use of the financial system but whose customers were spread well beyond the parochial precincts of the capital markets.

The decisive step from superstition to the supercomputer was about to be taken.

aAn excellent review of this matter appears in “The Triumph of Indexing,” a booklet published by the Vanguard Group of mutual funds in May 1995. This controversial subject receives more detailed treatment later in this chapter.

bIn a speech to the National Association of Realtors in May 1995, none other than the Chairman of the Federal Reserve Board, Alan Greenspan, confirmed the piggy bank metaphor: “It is hard to overestimate the importance of house price trends for consumer psyches and behavior. . . . Consumers view their home equity as a cushion or security blanket against the possibility of future hard times.” As a consequence of the growth in borrowing in the form of home equity loans, home equity has shrunk from 73% of home value in 1983 to around 55% at this writing, provoking what the July 10, 1995, issue of Business Week describes as “a major deterrent to buoyant spending.”

cWe exclude financial corporations from these calculations to avoid double-counting. Banks and other financial organizations re-lend to the nonfinancial sector most of the money they borrow.

dAs usual, Shakespeare got there first. In Act 1, Scene 1, lines 168–171 of Timon of Athens, the Jeweler says to Timon, “My Lord, tis rated/As those which sell would give; but you well know/Things of like value differing in their owners/Are prized by their masters.”

eIn Chapter 7 of Thaler, 1987, in fact, Thaler declared that von Neumann-Morgenstern utility had failed in psychological testing. See p. 139.

fThis bald assertion should be interpreted broadly. Cross-cultural problems and concerns for the health of the home country add to the value of domestic securities and detract from the value of foreign securities.

Notes

1. Personal conversation.

2. Bell, 1983, p. 1160.

3. “The recent rally in long-term bonds is driven by short-term speculation,” Roger Lowenstein, INTRINSIC VALUE, The Wall Street Journal, June 1, 1995, p. C1.

4. Keynes, 1936, p. 158.

5. Personal correspondence.

6. The following anecdote is from Thaler, 1991, pp. xi-xii.

7. Ibid., p. xii.

8. Statman, 1982, p. 451.

9. Thaler and Shefrin, 1981.

10. Shefrin and Statman, 1984.

11. Miller, 1987, p. 15.

12. Bernstein, 1986, p. 805.

13. Lakonishok, Shleifer, and Vishny, 1993.

14. Kahneman, Knetsch, and Thaler, 1990, pp. 170–177.

15. French and Poterba, 1989.

16. Keynes, 1936, pp. 155–156.

17. Bernstein, 1992, p. 34.

18. Ibid., p. 143.

19. For a detailed examination of this question, and related literature, see Shiller, 1989.

20. Vertin, 1974, p. 10.