Against the Gods: The Remarkable Story of Risk (48 page)

The auction went on for 112 rounds over three months and brought
the government $7.7 billion. Although some argued that the government could have raised more money if the FCC had prohibited the
alliances, the allocation of licenses in the end probably turned out to be
more efficient in terms of the economies of building franchises than it
would have been under the traditional procedure.

The motivation to avoid destructive bidding competitions is understandable. The highest bidder in an auction of this kind often suffers
what is known as the Winner's Curse-overpaying out of a determination to win. The Winner's Curse does not need a fancy auction-the
same curse may be visited on an investor in a hurry to buy a stock on
which someone has provided a hot tip. To avoid the curse, trading
sometimes takes place on computer screens in a manner that closely
resembles the spectrum auction. The players-usually large financial
institutions like pension funds or mutual funds-are anonymous, but all
bids and offers are displayed on the screen together with reservation
prices above which the investor will not buy and below which the
seller will not sell.

In January 1995, the publication Pensions and Investments reported
on another application of game theory in making investments. ANB
Investment Management & Trust in Chicago had introduced a strategy
explicitly designed to avoid the Winner's Curse. The chief investment
officer, Neil Wright, saying he had based the strategy on the Nash
Equilibrium, claimed that the Winner's Curse is usually associated with
stocks that have abnormally wide price ranges, which "means there is a
lot of uncertainty about how the company will do." A wide price range
also indicates limited liquidity, which means that a relatively small volume of buying or selling will have a significant impact on the price of
the stock. Wright accordingly planned to select his portfolio from
stocks with narrow trading ranges, an indication that they are priced around consensus views, with sellers and buyers more or less evenly
matched. The assumption is that such stocks can be bought for little
more than their consensus valuation.

Von Neumann and Morgenstern based The Theory of Games and
Economic Behavior on one essential element of behavior: the winnings
that will accrue to an individual who maximizes his utility-makes the
best of the available tradeoffs within the constraints set by the game
theory-will depend upon how much he "can get if he behaves 'rationally.' This `can get' [the winnings he can expect] is, of course, presumed
to be a minimum; he may get more if others make mistakes (behave
irrationall y)."19

This stipulation has posed a major problem for critics, including
distinguished behavioral psychologists like Daniel Ellsberg and Richard
Thaler, whom we will meet later. In a highly critical paper published in
1991, the historian Philip Mirowski asserted, "All is not well in the
House of Game Theory-in every dreamhouse a heartache-and signs
of pathology can no longer be ignored."20 He cites criticisms by Nobel
Prize winners Henry Simon, Kenneth Arrow, and Paul Samuelson. He
claims that game theory would never have amounted to anything had
von Neumann not sold it to the military; he even goes so far as to speculate, "Some laid the blame for the escalation of nuclear weaponry
directly at the door of game theory."21 Indeed, Mirowski claims that
Morgenstern was a "godsend" to von Neumann because he proposed
economists as an audience for game theory when no one else was interested. Mirowski is scathing about the naivete and oversimplification of
their definitions of "that sadly abused word," rationality, which he
describes as "a strange potage."22

Yet, game theory's assumption of rational behavior, and von
Neumann and Morgenstern's dream that such behavior can be measured and expressed in numbers, has unleashed a flood of exciting theories and practical applications. As the examples I have offered make
clear, its influence has reached far beyond the military.

During the 1950s and 1960s efforts were renewed to broaden the
study of rationality, particularly in economics and finance. Some of the
ideas advanced then seem lacking in substance today; in Chapters 16 and 17 we will subject those ideas to critical analysis. But we must
understand that, up to about 1970, much of the enthusiasm for rationality, for measurement, and for the use of mathematics in forecasting
emerged from the optimism that accompanied the great victories of the
Second World War.

The return of peacetime was heralded as an opportunity to apply the
lessons learned so painfully during the long years of depression and war.
Perhaps the dreams of the Enlightenment and the Victorian age might at
last come true for all members of the human race. Keynesian economics
was enlisted as a means of controlling the business cycle and promoting
full employment. The aim of the Bretton Woods Agreements was to
recapture the stability of the nineteenth-century gold standard. The
International Monetary Fund and the World Bank were set up to nourish economic progress among disadvantaged people around the world.
Meanwhile, the United Nations would keep peace among nations.

In this environment, the Victorian concept of rational behavior
regained its former popularity. Measurement always dominates intuition:
rational people make choices on the basis of information rather than on
the basis of whim, emotion, or habit. Once they have analyzed all the
available information, they make decisions in accord with well-defined
preferences. They prefer more wealth to less and strive to maximize utility. But they are also risk-averse in the Bernoullian sense that the utility
of additional wealth is inversely related to the amount already possessed.

With the concept of rationality so well defined and so broadly
accepted in intellectual circles, its transformation into rules for governing risk and maximizing utility was bound to influence the world of
investing and managing wealth. The setting was perfect.

The achievements that followed brought Nobel prizes to gifted
scholars, and the definitions of risk and the practical applications that
emerged from those achievements revolutionized investment management, the structure of markets, the instruments used by investors, and
the behavior of the millions of people who keep the system working.

,his chapter deals specifically with how to measure risk when we
invest in securities. Impossible as that may sound, quantification
of investment risk is a process that is alive, well, and regularly
practiced by professionals in today's world of globalized investing.
Charles Tschampion, a managing director of the $50 billion General
Motors pension fund, recently remarked, "Investment management is
not art, not science, it's engineering.... We are in the business of managing and engineering financial investment risk." The challenge for GM,
according to Tschampion, "is to first not take more risk than we need
to generate the return that is offered."' A high degree of philosophical
and mathematical sophistication lies behind Tschampion's words.

Throughout most of the history of stock markets-about 200 years
in the United States and even longer in some European countries-it
never occurred to anyone to define risk with a number. Stocks were
risky and some were riskier than others, and people let it go at that.
Risk was in the gut, not in the numbers. For aggressive investors, the
goal was simply to maximize return; the faint-hearted were content
with savings accounts and high-grade long-term bonds.