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 mod els 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 underperformance 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."" You will not find them on Wall $treet 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 Mere 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 fixedincome 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.
erivatives are the most sophisticated of financial instruments, the most intricate, the most arcane, even the most risky. Very 1990s, and to many people a dirty word.
Here is what Time magazine had to say in an April 1994 cover story:
[T]his fantastic system of side bets is not based on old-fashioned human hunches but on calculations designed and monitored by computer wizards using abstruse mathematical formulas ... developed by so-called quants, short for quantitative analysts.
We have just looked at the fantastic system of side bets based on old-fashioned human hunches. Now we turn to the fantastic system concocted by the quants.
Despite the mystery that has grown up about these instruments in recent years, there is nothing particularly modern about them. Derivatives go back so far in time that they have no identifiable inventors: no Cardano, Bernoulli, Graunt, or Gauss. The use of derivatives arose from the need to reduce uncertainty, and surely there is nothing new about that.
Derivatives are financial instruments that have no value of their own. That may sound weird, but it is the secret of what they are all about. They are called derivatives because they derive their value from the value of some other asset, which is precisely why they serve so well to hedge the risk of unexpected price fluctuations. They hedge the risk in owning things like bushels of wheat, French francs, government bonds, and common stocks-in short any asset whose price is volatile.
Frank Knight once remarked, "Every act of production is a speculation in the relative value of money and the good produced."' Derivatives cannot reduce the risks that go with owning volatile assets, but they can determine who takes on the speculation and who avoids it.
Today's derivatives differ from their predecessors only in certain respects: they are valued mathematically instead of by seat-of-the-pants methods, the risks they are asked to respond to are more complex, they are designed and managed by computers, and they are put to novel purposes. None of these features is the root cause of the dramatic growth in the use of derivatives or the headlines they have grabbed.
Derivatives have value only in an environment of volatility; their proliferation is a commentary on our times. Over the past twenty years or so, volatility and uncertainty have emerged in areas long characterized by stability. Until the early 1970s, exchange rates were legally fixed, the price of oil varied over a narrow range, and the overall price level rose by no more than 3% or 4% a year. The abrupt appearance of new risks in areas so long considered stable has triggered a search for novel and more effective tools of risk management. Derivatives are symptomatic of the state of the economy and of the financial markets, not the cause of the volatility that is the focus of so much concern.
Derivatives come in two flavors: as futures (contracts for future delivery at specified prices), and as options that give one side the opportunity to buy from or sell to the other side at a prearranged price. Sophisticated as they may appear in the fancy dress in which we see them today, their role in the management of risk probably originated centuries ago down on the farm. The particulars may have changed over time, but the farmer's fundamental need for controlling risk has not. Farmers cannot tolerate volatility, because they are perennially in debt. Their huge investments in land and equipment and in inventories of seed and fertilizer make bank financing unavoidable. Before the farmer sees any money coming his way, he has to pay for his inputs, plant his crop, and then, constantly fearful of flood, drought, and blight, wait months until harvest time. His great uncertainty is what the price will be when he is finally in a position to deliver his crop to the market. If the price he receives is below his cost of production, he might be unable to pay his debts and might lose everything.
The farmer is helpless before the risks of weather and insects, but he can at least escape the uncertainty of what his selling price will be. He can do that by selling his crop when he plants it, promising future delivery to the buyer at a prearranged price. He may miss out on some profit if prices rise, but the futures contract will protect him from catastrophe if prices fall. He has passed along the risk of lower prices to someone else.
That someone else is often a food processor who faces the opposite risk-he will gain if the prices of his inputs fall while the crop is still in the ground, but he wi
ll be in trouble if prices rise and boost the cost of his raw materials. By taking on the farmer's contract, the processor lets the farmer assume the risk that agricultural prices might rise. This transaction, involving supposedly risky contracts for both parties, actually lowers total risk in the economy.
On occasion, the other side of the deal is a speculator-someone who is willing to take over uncertainty from others out of a conviction about how matters will turn out. In theory at least, speculators in commodities will make money over the long run because there are so many people whose financial survival is vulnerable to the risks of volatility. As a result, volatility tends to be underpriced, especially in the commodity markets, and the producer's loss aversion gives the speculator a built-in advantage. This phenomen goes under the strange name of "backwardation."
In the twelfth century, sellers at medieval trade fairs signed contracts, called lettres de faire, promising future delivery of the items they sold. In the 1600s, Japanese feudal lords sold their rice for future delivery in a market called cho-ai-mai under contracts that protected them from bad weather or warfare. For many years, in markets such as metals, foreign exchange, agricultural products, and, more recently, stocks and bonds, the use of contracts for future delivery has been a common means of protection against the risks of volatile prices. Futures contracts for commodities like wheat, pork bellies, and copper have been trading on the Chicago Board of Trade since 1865.
Options also have a long history. In Book I of Politics, Aristotle described an option as "a financial device which involves a principle of universal application." Much of the famous Dutch tulip bubble of the seventeenth century involved trading in options on tulips rather than in the tulips themselves, trading that was in many ways as sophisticated as anything that goes on in our own times. Tulip dealers bought options known as calls when they wanted the assurance that they could increase their inventories when prices were rising; these options gave the dealer the right, but not the obligation, to call on the other side to deliver tulips at a prearranged price. Growers seeking protection against falling prices would buy options known as puts that gave them the right to put, or sell, to the other side at a prearranged price. The other side of these options-the sellers-assumed these risks in return for premiums paid by the buyers of the options, premiums that would presumably compensate sellers of calls for taking the risk that prices would rise and to compensate sellers of puts for taking the risk that prices would fall.
Against the Gods: The Remarkable Story of Risk Page 32