Analyst Overconfidence

We have observed that analyst forecasts are consistently overoptimistic. This bias in tandem with overconfidence can be extremely dangerous, particularly when stocks are highly valued.

It should be pretty obvious by now that analysts are far from being alone in their overconfidence. We have also seen that overoptimism is bred by overconfidence. Overoptimism shows itself regularly in many fields. In defense procurement, for example, major contracts often come in triple or quadruple die original estimates and the performance is often well below the original specifications. When President Nixon approved the Space Shuttle Program, one of the major goals was to be cost effective by putting a payload into space at a relatively low cost, thus requiring less use of cosdy rocket systems. In 1972, at the time of its approval, NASA estimated it would cost $200 a pound to put the shuttie and payload into orbit, and the space shutdes would fly 25 times a year. To the end of 1996, the actual costs were slighdy higher than projected-$10,000 a pound-while the number of flights averaged four or five a year. In a new submission, NASA is now estimating these costs will drop to $1,000 a pound-perhaps as low as $100. Any behevers?

Overoptimism often results from differences in estimates made from the inside rather than the outside view. A clear-cut example was demonstrated in an article in the Journal of Business Venturing The authors asked new entirepreneurs about their chances of success, and also queried them on what they thought the success rate was for similar startup companies. First, they found the entrepreneurs estimates of their own chances of hitting it big were completely unrelated to objective measures of success, such as a college education, prior management experience in die business, or the amount of capital they could put into the fledgling firms. Second, the entrepreneurs were strikingly overoptimistic. Over 80% believed their chances of success were 70% or higher. By comparison, the chance they attributed to similar businesses was 59%. They were far too optimistic about both their own and the average

To not rely on the skyrocketing earnings estimates of a company such as Yahoo, on the cutting edge of Internet technology, many analysts would argue, is vasdy unfair to current shareholders and potential buyers. Ironically, rapid technology change, accompanied by rapierlike growth, makes the forecasting process even more difficult dian for more mundane companies.

This leads back to the important question of overconfidence.

survival rate of start-up business. According to Dun & Bradstreet, the survival rate of new firms is 33% after five years.

Overoptimism shows up in many other parts of the 1 world. With capital spending projects, optimistic bias is a familiar fact of life. The typical project finishes late, comes in over budget, and fails to achieve its initial goal. Grossly optimistic errors appear to be very frequent with new technologies or other projects where the firm is in an unfamiliar situation. A Rand 11 study some years back examined the cost of new types of plants in the energy field. The norm was that actual construction costs doubled initial estimates, while 80% of the projects failed to gain their projected market share.

A psychological study examining the cause of this type of failure concluded that most companies demanded a worst-case scenario for a capital spending project. "But the worst case forecasts are almost always too optimistic. When managers look at the downside, then generally describe a mildly pessimistic future rather than the worst possible fu-ture."5"

A review of the literature on overconfidence tums up three major reasons for a wide-ranging optimistic bias. First, people have unrealistic optimism about future events. Second, they have unreaUstically positive self-evaluations. Third, they have unrealistic confidence in their ability to control a situation. Thus, for every positive trait-such as managerial risk-taking, safe driving, or a sense of humor-they rank themselves above the median. People also overestimate the skills and the resources at their disposal to ensure a favorable outcome, while they underestimate the likelihood of problems affecting them personally. A security analyst is well aware that stocks trading in the stratosphere will collapse if eamings come in under target. But he is also confident that he knows everything there is to know about the high-flyer he is recommending, and so strongly believes it wont happen to him. A good rale to train yourself to follow:

RULE 9

Be realistic about the downside of an investment, recognizing our human tendency to be both overly optimistic and overly confident. Expect the worst to be much more severe than your initial projection.

In this chapter, we have looked at the striking errors in analysts forecasts, errors so high that they render the majority of current investment methods inoperable. We have also seen that in spite of high error rates

being recognized for decades, neither analysts nor investors who religiously depend on them have altered their methods in any way.

The problem is not unique to analysts or market forecasters. We have also looked at how pervasive it is in many professions where information is difficult to analyze, as well as how hard the problem is to recognize, let alone change. Finally, we have found overoptimism to be a strong component of expert forecasts, both within and outside of the stock market.

Next, a look at the market reaction to errors in analysts forecasts. The results, Im sure, will prove interesting.