the recession levels projected in the weeks following the October 19 debacle.

Stock fundamentals were encouraging. The P/E of the S&P 500 was a little over 13 times eamings, down 8 1 from the 20 times eamings just prior to the 1987 crash, and below the long-term average of 15 to 16. The underlying fundamentals of the two periods were dramatically different. 1929 it wasnt. Investors who followed the representativeness bias missed an enormous buying opportunity: by July, 1997, the market quadrapled from that time.

The representativeness heuristic covers a number of common decision-making errors. Kahneman and Tversky defined this heuristic as a subjective judgment of the extent to which the event in question "is similar in essential properties to its parent population" or "reflects the salient features of the process by which it is generated." People often judge probabilities "by the degree to which A is representative of B, that is, by the degree to which A resembles B."

What are A and B? It depends. If you are estimating the probability that A came from B, A might be a person and might be a group, say of doctors. The judgment you want to make in this case is the probability A is also a doctor. Or A might be an event and might be a potential cause. Again you are judging the probability that A comes from B. A, for example, would be the similarity or representativeness in peoples minds of the 1987 crash to which, in this case, would be the 1929 crash and depression.

Because the definition of representativeness is abstract and a little hard to understand, lets look at some more concrete examples of how this heuristic works, and how it can lead to major mistakes in many situations.

First, it may give too much emphasis to the similarities between events (or samples), but not to the probabiHty that they will occur. Again looking at the 1987 crash, it appeared similar to 1929 in its stunning dechne, but this by itself did not mean that a Great Depression would follow. In fact, as we have seen, there have been many crashes, but only one Great Depression. Still, the dramatic event of the 1929 Crash followed by the Great Depression was an ove owering image. After the 1987 crash, people did not step back and try to logically assess what the probabilities were that the next event would occur in an identical manner. Rather, by using the representativeness heuristic, or mental shortcut, they assumed this would be the outcome.

Second, representativeness may reduce the importance of variables that are critical in determining the events probability. Again using the crash as an illustration, the major differences between the situations in

1987 and 1929, oudined in the Forbes article, were downplayed, with the focus solely on the markets plunge.

This type of representativeness bias occurs time and again in the marketplace. During the Gulf Crisis in the last half of 1990, for example, the stock market fell dramatically on the fears of a worldwide shortage of oil. The seizing of the Kuwaiti oil fields by Iraq, and the subsequent embargo on Iraqi oil, triggered the bias for both investors and the media. The surface similarities to the past indicated an oil shortage, followed by a skyrocketing increase in price, culminating in runaway inflation, as was the case in 1981, or a severe recession as in 1973-1974. Markets plunged, as investors fearfully recalled the battered sales of large cars and other gas-guzzlers including yachts (whose prices dropped 8 1 ) as well as other economic horrors.

The representativeness bias worked in an identical manner to the way it had after the 1987 crash. Yet 1990 was dramatically different from 1973 or 1981.

I warned about the dangers of false parallels in a column written at the time. While it was impossible to predict the outcome of the Persian Gulf Crisis, the world was not facing a major protracted increase in oil prices.

Still, market pundits immediately compared this oil crisis with those of 1973/1974 and 1979/1980. Back in 1980, for example, od experts stated that crude would reach $100 a barrel by the end of the decade, at the latest. Then, too, leading dailies ran front-page series for months on how higher oil prices would permanentiy damage the economy. Some of the statistics conjured up to back the predictions were terrifying. One showed that at the then-current price of oil, almost the entire capital of the Western world would flow into the coffers of OPEC (Organization of Petroleum Exporting Countries) members. Another demonstrated that Saudi Arabia would accumulate more capital in six or seven years than the value of all stocks on the NYSE.

What actually happened? By the late 1980s oil had dropped to as low as $12 a barrel. Fear sells newspapers and keeps people glued to the tube, but fear does not make money in the stock market.

But all of this was forgotten as the crisis developed in the late summer of 1990. In fact, the differences between the Gulf Crisis and the two previous oil crises were remarkable. In 1990 the world was facing an oil glut, not the shortages of the two earlier occasions. Oil prices, rather than tripling as they did in the seventies, were up only about 30% in the 1990 crisis. Too, this time around the OPEC members had not banded together to increase prices. Instead they had mostiy condemned the Iraqi aggression and felt threatened by it. The OPEC cartel indicated it would

make up the Iraq-Kuwait difference to keep prices from rising further. With the 50-year-plus supply the Saudis and some of the other producers had, and their pressing need for hard cash, economic considerations ranked up there with altruism. Finally, there was a unanimity among the major powers in response to the crisis that had not occurred in well over a century.

The analysis strongly indicated that oil prices were not destined to move higher for long, if at all. The panic that gripped many investors had created the finest buying opportunity of the decade.

You can see the representativeness bias resulted in a near identical investor reaction to the Gulf Crisis as it did to the 1987 crash. First, people put undue weight on the surface similarities between the potential oil crisis of 1990 and those of 1973/1974 and 1980. Secondly, investors again downplayed the critical differences between the two periods the article outiined, which were far more important than the casual resemblances. Again, the bias contributed to major investor errors in decisionmaking.

As Im sure you have guessed, the representativeness heuristic can apply just as forcefully to a company or an industry as to the market as a whole. Here is one such an example:

In 1993 Dell Computer collapsed on Wall Street, losing 50% of its value in months. One day it had a market capitalization of $4.6 billion; six months later, it was just over $2.2 billion. Same company but worth less than half as much, and trading at only 4.6 times the previous years eamings. What caused the drop? Eamings were weak, as the company took some major charges while repositioning its personal computer lines, and restructuring its marketing.

What probably happened was this: two other industry leaders, IBM and Digital Equipment Corporation (DEC), were weak, and investors lumped the three companies together. IBM was in temporary trouble, while DECS was more serious. Dell was not. It was a very different kind of company with different products. Its repositioning was fabulously successful and it went on to become a major player in the personal computer (PC) industry. If you had bought it at its 1993 low, you would have increased your money more than 59-fold by late 1997. The representativeness bias worked the same way as in the two previous examples.

Kahneman and Tverskys findings, which have been repeatedly confirmed, are particularly important to our understanding of stock market errors and lead us to this mle of investing: