|
ARE SECURITY ANALYSTS
FUNDAMENTALLY
CLAIRVOYANT?
Forecasting future earnings is the security analysts’ raison
d’être. As
Institutional Investor
put it, “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 earnings growth is,” one analyst told me, “a
most reliable indicator of future earnings growth.” If
management is really skillful, there is no reason to think that
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. While it sounds suspiciously like an
argument used by technical analysts, fundamentalists pride
themselves on the fact that it is based on specific, proven
company performance.
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 1980–90 period, this would not have helped you at
all in predicting what growth they would achieve in the 1990–
2000 period. And knowing the fast growers of the 1990s has
not helped analysts find the fast growers of the first decade
of the twenty-first century. 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!
“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, Kodak, Nortel
Networks, Xerox, and dozens of other firms that chalked up
consistent high growth rates until the roof fell in. I hope you
remember not the current exceptions, but rather the rule:
Many in Wall Street refuse to accept the fact that no reliable
pattern can be discerned from past records to aid the analyst
in predicting future growth. Even during the boom years of
the 1990s, only one in eight large companies managed to
achieve consistent yearly growth. And not even one
continued to enjoy growth into the first years of the new
millennium. Analysts can’t predict consistent long-run
growth, because it does not exist.
A good analyst will argue, however, that there’s much
more to predicting than just examining the past record. Some
will even admit that the past record is not a perfect
measurement. Rather than examine 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 of the most respected Wall Street firms engaged in
fundamental analysis. We asked these firms for their
estimates of the future one-year and five-year earnings for a
large sample of S&P 500 companies. 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 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 naive 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. If you used this naive forecasting model, you would
often make smaller errors in forecasting long-run earnings
growth than by using professional analysts’ forecasts.
Our method of determining the efficacy of the security
analyst’s diagnoses of his companies 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 naive mechanism involving no expertise
at all. Sometimes these naive 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. Although this system misses every
turning point in the weather, 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 felt that 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.
The analysts fought back gamely. They complained that it
was unfair to judge their performance on a wide cross section
of industries, because earnings for high-tech 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. This led to the second major
finding of our study: Not one industry 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 no consistency in their pattern of
performance was found. Analysts who did better than
average one year were no more likely than the others to make
superior forecasts in the next year.
These findings have been confirmed by several other
researchers. For example, Michael Sandretto of Harvard and
Sudhir Milkrishnamurthi of MIT completed a massive study
of the one-year forecasts of the 1,000 most widely followed
companies. Their staggering conclusion was that the error
rates each year were remarkably consistent and that the
average annual error of the analysts was 31.3 percent over a
five-year period. Financial forecasting appears to be a science
that makes astrology look respectable.
Amid all these accusations is a deadly serious message:
Security analysts have enormous difficulty in performing
their basic function of forecasting company earnings
prospects. Investors who put blind faith in such forecasts in
making their investment selections are in for some rude
disappointments.
Do'stlaringiz bilan baham: | 
