RULE 22

Look beyond obvious similarities between a current investment situation and one that appears equivalent in the past. Consider other important factors that may result in a markedly different outcome.

The Law of Small Numbers

The representativeness bias is responsible at least in part for a number of other major and oft-repeated errors. All mutual fund organizations worlc from the principle that investors flock to better-performing mutual funds-even though financial researchers have shown that the "hot" funds in one time period are often the poorest performers in another. The final verdict on the sizzling funds in the 1982/1983 market was disastrous. Ditto for the aggressive-growdi funds of 1991 to 1997. Investors lost billions of dollars in these funds. Many, although far more risky, could not hold a candle to the long-term records of many conservative, blue-chip mutual funds.

Still, people are continually enticed by such "hot" performance, even if it lasts for brief periods. Because of this susceptibility, brokers or analysts who have had one or two stocks move up 8 1 , or technicians who call one turn correctly, are believed to have established a credible record and can readily find market followings.

Likewise, an advisory service that is right for a brief time can beat its drums loudly. One market-letter writer was featured prominendy in the Sunday New York Times for being bearish in July of 1996, as the market dropped rapidly. He was right for three weeks but missed the enormous rally of the prior 18 months, as well as the subsequent rise for the balance of 1996, which kept him out of the market as it spiked 80%.

In fact, it doesnt matter if die advisor is wrong repeatedly, the name of the game is to get a dramatic prediction out there. A well-timed call can bring huge rewards to a popular newsletter writer. Eugene Lerner, a former finance professor who heads Disciplined Investment Advisors, a market-letter writer, speaking of what making a bearish call in a declining market can do, said, "If the market goes down for the next three years youll be as rich as Croesus... . The next time around, everyone will listen to you." With hundreds and hundreds of advisory letters out there someone has to be right. Again, its just the odds.

Elaine Garzarelli gained near immortality when she pu ortedly "called" the 1987 crash. Although, as the market strategist for Shearson

Lehman, her forecast was never pubhshed in a research report, nor indeed communicated to its chents, she still received widespread recognition and publicity for this call, which was made in a short TV interview on CNBC.

Since this "brilliant call," her record, according to a fellow strategist, "has been somewhat mixed, like most of us."* Still, her remark on CNBC that the Dow could drop sharply from its then 5300 level rocked an already nervous market on July 23, 1996. What had been a 40-point gain for the Dow tumed into a 40-point loss, a good deal of which was attributed to her comments. Only a few days earlier, Ms. Garzarelli had predicted the Dow would rise to 6400 from its then value of 5400. Even so, people widely followed her because of "the great call in 1987."

Stan Weinstein, editor of The Professional Tape Reader, an advisory letter headquartered in Hollywood, Florida, advertises week after week that the market is heading south. He naturally tells potential subscribers that following his advice will make them mega-bucks. Mr. Weinsteins ti-ack record leaves much to be desired. According to the Hulbert Financial Digest, his advice has significantly underperformed the mar-ket.7

The tmth is, market-letter writers have been wrong in their judgments far more often than they would like to remember. However, advisors understand that the public considers short-term results meaningful when they are, more often than not, simply chance. Those in the public eye usually gain large numbers of new subscribers for being right by random luck.

Which brings us to another important probability error that falls under the broad mbric of representativeness. Amos Tversky and Daniel Kahneman call this one the "law of small numbers."* Examining journals in psychology and education, they found that researchers systematically overstated the importance of findings taken from small samples. The statistically valid "law of large numbers" states that large samples will usually be highly representative of the population from which they are drawn; for example, public opinion polls are fairly accurate because they draw on large and representative groups. The smaller the sample used, however (or the shorter the record), the more likely the findings are chance rather than meaningful.

Yet the Tversky and Kahneman study showed that typical psychological or educational experimenters gamble their research theories on samples so small that the results have a very high probability of being chance. This is the same as gambUng on the single good call of an investment advisor. The psychologists and educators are far too confident in the significance of results based on a few observations or a short pe-

riod of time, even though they are trained in statistical techniques and are aware of the dangers.

Note how readily people overgeneraUze the meaning of a small number of supporting facts. Limited statistical evidence seems to satisfy our intuition no matter how inadequate the depiction of reality. Sometimes the evidence we accept runs to the absurd. A good example of the major overemphasis on small numbers is the almost blind faith investors place in governmental economic releases on employment, industrial production, the consumer price index, the money supply, the leading economic indicators, et cetera.

These statistics frequently trigger major stoclc- and bond-market reactions, particularly if the news is bad. For example, investors are concemed about the possibility of rising prices. If the unemployment rate drops two-tenths of one percent in a month when it was expected to be unchanged, or if industrial production climbs slighdy more than the experts expected, stock prices can fall, at times sharply.

Should this happen? No. Flash statistics, more times than not, are near worthless. Initial economic and Fed figures are revised significandy for weeks or months after their release, as new and "better" information flows in. Thus, an increase in the money supply can tum into a decrease, or a large drop in the leading indicators can change to a moderate increase. These revisions occur with such regularity you would think that investors, particularly pros, would treat them with the skepticism they deserve.

Alas, the real world refuses to follow the textbooks. Experience notwithstanding, investors treat as gospel all authoritative-sounding releases that they think pinpoint the development of important trends.

An example of how instant news threw investors into a tailspin occurred in July of 1996. Preliminary statistics indicated the economy was beginning to gain steam. The flash figures showed that GDP (gross domestic product) would rise at a 3% rate in the next several quarters, a rate higher than expected. Many people, convinced by these statistics that rising interest rates were imminent, bailed out of the stock market that month. To the end of that year, the GDP growth figures had been revised down significantly (unofficially, a minimum of a dozen times, and officially at least twice). The market rocketed ahead to new highs to August 1997, but a lot of investors had retreated to the sidelines on the pre-Hminary bad news.

Just as irrational is the overreaction to every utterance by a Greenspan or other senior Fed or govemment official, no matter how offhanded. Like ancient priests examining chicken entrails to foretell events, many pros scmtinize every remark and act upon it immediately, even though