EMT may remain valuable to economists in explaining portions of market processes—the public capital markets alternately may involve both random and non random components. But this partial validity must not be misunderstood to suggest that markets are “relatively efficient,” “reasonably efficient,” “sufficiently efficient,” or “more efficient than not” at any moment in time, as many devotees of EMT have been forced to argue since the market crash of 1987 shookconfidence in that theory.
Since 1987, a new generation of economists has arisen in prominent universities to challenge EMT. Led by Robert Shiller of Yale, a school of thought called behavioral finance draws on a wide range of disciplines—including economics, psychology, biology, demography, sociology, and history—to challenge the essentially mathematical underpinnings of EMT.
The pioneers of behavioral finance have found substantial evidence supporting two of Buffett’s long-held and most commonsense propositions. The first is that while stockprices over short horizons bounce around a lot, wedging price and value, over long horizons the price must correspond to value. As Andrei Shleifer of Harvard puts it, summarizing the studies: “Stocks with very high valuations relative to their assets or earnings (growth or glamour stocks), which tend to be stocks of companies with extremely high earnings growth over the previous several years, earn relatively low riskadjusted returns in the future, whereas stocks with low valuations (value stocks) earn relatively high returns.”
The second is evidence showing that investing in the latter group of stocks (mislabeled “value stocks,” but the label is useful to simplify the discussion) offers superior returns over long horizons. However measured, the evidence Shleifer and his colleagues compiled shows that “value” stocks outperform “growth” stocks by spreads of about 8 to 10% annually over long horizons.
As early as 1981, Shiller showed that stockmark et prices are too volatile to accord with EMT. Shiller’s peers at that time skewered him for this blasphemy, but his research has held up and attracted a still small but growing following, including former Harvard professor Lawrence Summers, who became secretary of the treasury.
Shiller examined the relationship between price changes and subsequent cash paid to stockholders and found remarkable irregularity (bouncing around) in price changes in contrast to remarkable smoothness in the cash stream.
Shiller and his colleague John Campbell recognize that some of the price changes are due to changes in fundamental information and to uncertainty about the future trends of cash flows. But taking account of these factors, Shiller and Campbell estimated that only 27% of the annual return volatility in U.S. stockmark ets is justified in terms of fundamental information. Campbell followed up this research with John Ammer by using more recent data and reduced the estimate to only 15%.
Markets may be relatively efficient only on some days but not on all days or may be relatively efficient for some stocks but not for others. Even if we are more generous than the 15 to 27% suggested by these studies and say EMT is 80% correct, it is a grave mistake to use market efficiency as the basis of a managerial or investor game plan. Buffett sums it up: “Observing correctly that the market was frequently efficient,” EMT devotees “went on to conclude incorrectly that it was always efficient. The difference between these propositions is night and day.” That difference between night and day is all that Graham and Buffett need to recognize. Neither is enthused by mathematical accounts of markets, except to agree that EMT does not explain all of market behavior.
Buffett quotes one of Charlie Munger’s favorite sayings to describe the modern economist’s penchant for building EMT and related mathematical models of stockmark ets: “To a man with a hammer, every problem looks like a nail.” Graham quotes Aristotle: “It is the markof an educated mind to expect that amount of exactness which the nature of the particular subject admits. It is equally unreasonable to accept merely probable conclusions from a mathematician and to demand strict demonstration from an orator.”
Graham concludes that “the workof a financial analyst falls somewhere in the middle between that of a mathematician and an orator.” The vanguard theorists of behavioral finance stand a better chance of finding that middle road than do the devotees of EMT, but they admit they still have a long way to go in understanding investors and markets, a task that is likely to get harder rather than easier.
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