Are Security Analysts Fundamentally Clairvoyant?
Forecasting future earning is the security analysts' raison d'être. As a top Wall Street professional put it in his fraternity magazine, Institutional Investor: “Expectation of future earnings is still the most important single factor affecting stock prices.” Growth in earnings and therefore in the ability to pay dividends is the key element needed to estimate a stock's firm foundation of value. The analyst who can make accurate forecasts of the future will be richly rewarded. “If he is wrong,” Institutional Investor puts it,” a stock can act precipitously, as has been demonstrated time and time again. Earnings are the name of the game and always will be.”
To predict future directions, analysts generally start by looking at past wanderings. “A proven score of past performance in earning growths is,” one analyst told me, “a most reliable indicator of future earnings growth.” If management is really skillful, there is no reason to think it will lose its Midas touch in the future. If the same adroit management team remains at the helm, the course of future earnings growth should continue as it has in the past, or so the argument goes.
Such thinking flunks in the academic world. Calculations of past earnings growth are no help in predicting future growth. If you had known the growth rates of all companies during, say, the 1970-80 period, this would not have helped you at all in predicting what growth they would achieve in the 1980-90 period. And knowing the fast growers of the nineties. This startling result was first reported by British researchers for companies in the United Kingdom in an article charmingly titled “Higgledy Piggledy Growth.” Learned academicians at Princeton and Harvard applied the British study to U.S. Companies – and, surprise, the same was true here!
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| An old bank. Photo by Elena |
“IBM,” the cry immediately went up. “Remember IBM!” I do remember IBM: a steady high grower for decades. For a while it was a glaring exception. But after the mid-1980s even the mighty IBM failed to continue its dependable growth pattern. I also remember Polaroid and dozens of other firms that chalked up consistent large growth rates until the roof fell in. I hope you remember not the exception but rather the rule: There is no reliable pattern that can be discerned from past records to aid the analyst in predicting future growth.
A good analyst will argue, however, that there's much more to predicting than just examining the past record. Rather than measure every factor that goes into the actual forecasting process, John Cragg and I decided to concentrate on the end result: the prediction itself.
Donning our cloak of academic detachment, we wrote to nineteen major Wall Street firms engaged in fundamental analysis. The nineteen firms, which asked to remain anonymous, included some of the major brokerage firms, and banks engaged in trust management. They are among the most respected names in the investment business.
We requested – and received – past earnings predictions on how these firms felt earnings for specific companies would behave over both a one-year and a five-year period. These estimates, made at several different times, were then compared with actual results to see how well the analysts forecast short-run and long-run earnings changes. The results were surprising. Bluntly stated, the careful estimates of security analysts (based on industry studies, plant visits, etc.) do very little better than those that would be obtained by simple extrapolation of past trends, which we have already seen are no help at all. Indeed, when compared with actual earnings growth rates, the five-year estimates of security analysts were actually worse than the predictions from several naïve forecasting models.
For example, one placebo with which the analysts' estimates were compared was the assumption that every company in the economy would enjoy a growth in earnings approximating the long-run rate of growth of the national income. It often turned out that if you used that naïve forecasting model you would make smaller errors in forecasting long-run earnings growth than by using the professional forecasts of the analysts.
Our method of determining the efficacy is exactly the same as was used before in evaluating the technicians' medicine. We compared the results obtained by following the experts with the results from some naïve mechanism involving no expertise at all. Sometimes these naïve predictors work very well. For example, if you want to forecast the weather tomorrow you will do a pretty good job by predicting that it will be exactly the same as today. It turns out that while this system misses every one of the turning points in the whether, for most days it is quite reliable. How many weather forecasters do you suppose do any better?
When confronted with the poor record of their five-year growth estimates, the security analysts honestly, if sheepishly, admitted that five years ahead is really too far in advance to make reliable projections. They protested that while long-term projections are admittedly important, they really ought to be judged on their ability to project earnings changes one year ahead.
Believe it or not, it turned out that their one-year forecasts were even worse than their five-year projections. It was actually harder for them to forecast one year ahead than to estimate long-run changes.
The analysts fought back gamely. They complained that it was unfair to judge their performances on a wide cross section on industries, since earnings for electronic firms and various cyclical companies are notoriously hard to forecast. “Try us on utilities, one analyst confidently asserted. So we tried it, and they didn't like it. Even the forecasts for the stable utilities were far off the mark. Those the analysts confidently touted as high growers turned out to perform much the same as the utilities for which only low or moderate growth was predicted. This led to the second major finding of our study: There is not one industry that is easy to predict.
Moreover, no analysts proved consistently superior to the others. Of course, in each year some analysts did much better than average, but there was no consistency in their pattern of performance. Analysts who did better than average one year were no more likely than the others to make superior forecasts in the next year.
My findings with Cragg have been confirmed by several other researchers. For example, Michael Sandaretto of Harvard and Sudhir Milkrishnamurthi of M.I.T. Completed a massive study of the one-year forecasts of the most widely followed companies between 1977 and 1981. The number of companies monitored was about 1,000 each year, and, in general, estimates were available from five or six analysts for each company. All estimates were made for the then current year, so that 1981 estimates had been made early in 1981. The staggering conclusion of the study was that the average annual error of the analysts was 31.3 percent over the five-year period. The error rates each year were remarkably consistent – the lowest error rate was 27.6 percent in 1978, the highest 33.5 percent in 1981. Financial forecasting appears to be a science that makes astrology look respectable.
Amidst all these accusations and counter-assertions, there is a deadly serious message. It is this: Security analysts have enormous difficulty in performing their basic function of forecasting earnings prospects for the companies they follow. Investors who put blind faith in such forecasts in making their investment selections are in for some rude disappointments.
Burton G. Malkiel. A Random Walk Down Wall Street, including a life-cycle guide to personal investing. First edition, 1973, by W.W. Norton and company, Inc.
