A random Walk Down Wall Street: The Time-Tested Strategy for Successful Investing

in advance
when a bubble is inflating and when it will deflate. Identifying
asset-price bubbles from an examination of historical prices is
simply not possible. And tremendous uncertainty regarding
the measurement of the justifiable price of any asset makes it
extremely difficult to determine whether market prices can be
supported by fundamentals. Some spectacular price increases
proved to be well supported after the fact.
None of the EMH critics distinguish mispricings that are
obvious after the fact from those that were clear in advance.

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We know now that Internet stocks were wildly overpriced
during the end of 1999 and early 2000. We know now that
real estate prices in the United States were wildly overpriced
in 2006 and early 2007. We know now that there would have
been enormous opportunities for profit by selling short
Internet stocks in early 2000 and selling overpriced homes
and commercial real estate in 2007. But neither of those
mispricings was nearly as obvious before the crash occurred
in both markets.
Critics would argue that the technology-Internet stock-
market bubble was easy to identify as it was inflating. Robert
Shiller published his book 
Irrational Exuberance
in early
2000, just at the peak of the market. True, but the same
models that identified a bubble in early 2000 also identified a
vastly “overpriced” stock market in 1992, when low dividend
yields and high price-earnings multiples suggested that long-
run equity returns would be close to zero in the United
States. In fact, from 1992 through 2004, annual stock market
returns were over 11 percent, well above their historical
average. In December of 1996, when Chairman Greenspan
gave his “irrational exuberance” speech, those same models
predicted 
negative
long-run equity returns. From the date of

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the chairman’s speech through December 2009, the stock
market returned 7 percent per year, even after withstanding
two sharp bear markets. It is only in retrospect that we know
that it was during 1999 and early 2000 when stock prices
were “too high.”
Again it is true that many observers did recognize that a
bubble in real estate prices was inflating during 2006. But
such worries were expressed much earlier in the decade, and
there were numbers of observers, including Alan Greenspan
and Ben Bernanke, former and current chairmen of the Board
of Governors of the Federal Reserve System, who vigorously
denied that a bubble existed. The issue is not whether prices
turned out to be incorrect—they often do. Markets are based
on expectations, and prices often turn out to be “incorrect.”
The question is whether such instances of asset-priced
bubbles can reliably be identified in advance. The failure of
professional portfolio managers to beat the market is
powerful evidence that even professional investors cannot
reliably identify bubbles in advance.
With respect to the evidence reviewed in this chapter
indicating that future returns are somewhat predictable, there
are several points to be made. First, considerable questions

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surround the long-run dependability of these effects. Many
could be the result of “data snooping,” letting the computer
search through the data sets of past securities prices in hopes
of finding some relationships. Thus, many of the predictable
patterns that have been discovered may simply be the result
of data mining—beating the data set in every conceivable way
until it finally confesses.
Second, even if there is a dependable predictable
relationship, it may not be exploitable by investors. For
example, the transaction costs involved in trying to capitalize
on the January Effect are sufficiently large that the
predictable pattern is not economically meaningful. Third, the
predictable pattern that has been found, such as the dividend
yield effect, may simply reflect general economic fluctuations
in interest rates or, in the case of the small-firm effect, an
appropriate premium for risk. Finally, if the pattern is a true
anomaly, it is likely to self-destruct as profit-maximizing
investors seek to exploit it. Indeed, the more profitable any
return predictability appears to be, the less likely it is to
survive.
An exchange between Robert Shiller, a skeptic about
market efficiency, and Richard Roll, an academic economist

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who was also a businessman running billions of dollars of
investment funds, is quite revealing. After Shiller stressed the
importance of fads and inefficiencies, Roll responded as
follows:
I have personally tried to invest money, my client’s
money and my own, in every single anomaly and
predictive device that academics have dreamed up…. I
have attempted to exploit the so-called year-end
anomalies and a whole variety of strategies supposedly
documented by academic research. And I have yet to
make a nickel on any of these supposed market
inefficiencies…. I agree with Bob that investor
psychology plays an important role. But, I have to keep
coming back to my original point that a true market
inefficiency ought to be an exploitable opportunity. If
there’s nothing investors can exploit in a systematic
way, time in and time out, then it’s very hard to say that
information is not being properly incorporated into
stock prices…. Real money investment strategies don’t
produce the results that academic papers say they
should.

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Roll’s final point was underscored for me during an
exchange I had with a portfolio manager who used the most
modern quantitative methods to run his portfolio on the basis
of all the statistical work done by academics and
practitioners. He “back-tested” his technique with historical
data over a twenty-year period and found that it
outperformed the Standard & Poor’s 500-Stock Index by
three percentage points per year. But when he started using
those quantitative methods with real money, his results were
quite different. Over the next twenty-year period, he barely
managed to equal the S&P return after expenses. This was an
extraordinary performance and ranked him in the top 10
percent of all money managers. Yet the results make clear that
techniques that work on paper do not necessarily work when
investing real money and incurring the transactions costs that
are involved in the real world of investing. As this portfolio
manager sheepishly told me, “I have never met a back test I
didn’t like.” But let’s never forget that academic back tests
are not the same thing as managing real money.
As long as there are stock markets, mistakes will be made
by the collective judgment of investors. And undoubtedly,
some market participants are demonstrably less than rational.

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As a result, pricing irregularities and predictable patterns in
stock returns can appear over time and even persist for short
periods. But I suspect that the end result will not be an
abandonment of the belief of many in the profession that the
stock market is remarkably efficient in its utilization of
information.
The EMH’s basic underlying notion that there are obvious
opportunities to earn excess risk-adjusted returns and that
people will flock to exploit them until they disappear is as
reasonable and commonsense as anything put forward by the
EMH’s critics. 
Systematically beating the market remains
really hard, and the EMH remains an extremely useful
working hypothesis.
If any $100 bills are lying around, they
will not be there for long.

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