Financial theory is in flux. Ideas that once were widely accepted among financial economists are in dispute. In particular, the efficient-markets hypothesis — which dominated academic thinking about finance for decades and influenced the investment industry while never fully being embraced by it — has faced growing skepticism in recent years, and all the more so in the aftermath of the market mayhem of 2008.
The efficient-markets hypothesis, or EMH, holds that the price of a financial asset swiftly and surely reflects information relevant to that asset. Most often applied to a particular type of asset, namely stocks, the EMH suggests there is no way to beat the market through stock-picking skill, at least not with any regularity. Rather, in this view, stock prices move in a “random walk,” buffeted by new information that was not available before (and which may be favorable or unfavorable, versus expectations).
Wall Street has long held a profound ambivalence toward such theoretical randomness. The EMH’s broad dismissal of stock-picking has rarely generated enthusiasm in an industry built, in no small part, on precisely that activity. However, the EMH gave intellectual impetus to the development of index funds, and also jibed well with Modern Portfolio Theory’s emphasis on diversification across sectors and asset classes. In addition, by downplaying concerns about bubbles and misallocations of resources, the EMH offered a basis for regulators to maintain a relatively light hand.
The EMH emerged as a bold new idea in the 1960s, became the dominant paradigm of academic finance in the 1970s and then gradually faced growing opposition over the next few decades. Much debate hinged on just how efficient markets really are and whether possible variations from efficiency constitute minor exceptions to a generally true rule or major holes in an overly abstract doctrine. In recent decades, behavioral finance has emerged as a serious theoretical contender with its emphasis on psychological quirks that could undermine the market’s fast and accurate data processing.
Skepticism about the EMH has been heightened by the financial crisis. Wild swings in the prices of assets cast doubt on assertions that market valuations tend to be broadly in line with intrinsic values. Thus, behavioral finance has gotten a boost, as have other theoretical approaches, such as looking more closely at how the institutions involved in financial markets work (or don’t work).
Still, whatever emerges from the current intellectual disarray is likely to bear some imprint of the idea that markets are efficient. No alternative approach seems near to producing a comprehensive, agreed-upon view of how markets function, nor a decisively convincing method of beating the market in defiance of efficiency’s logic. Plus, the EMH’s validity seems to depend partly on people not believing it; if markets are seen as efficient, there’s less motivation for the information-gathering that makes them efficient. Paradoxically, then, attacks on the EMH could actually increase its relevance.
In any event, the history of the efficient-markets hypothesis — both its rise to dominance and its subsequent piecemeal retreat into an unsettled position — indicate that even highly esoteric ideas from academic finance have an impact on how financial practitioners go about their business far beyond the walls of academia.
As far back as 1900, a French mathematician named Louis Bachelier was looking closely at securities prices and finding that they lack an observable or predictable pattern. As it happened, this work anticipated the math used by Einstein five years later in elucidating the particle behavior known as Brownian motion. But if Bachelier was slightly ahead of his time in physics, he was way ahead of his time in finance, and his “Th?orie de la Sp?culation” languished in obscurity for more than half a century.
In the next few decades, though, a few researchers were pushing in a similar direction. In 1933, economist Alfred Cowles III sorted through massive data to conclude that nobody had been forecasting the stock market accurately. The next year, researcher Holbrook Working published a study showing historic stock prices to be about as useful for prediction as lottery numbers.
Cowles did a 1944 study covering longer time periods and still showing no evidence of anyone knowing how to forecast the stock market. In 1953, British statistician Maurice Kendall looked at equity and commodity prices and found that random moves were “so large as to swamp any systematic effect which may be present.”
During the 1950s, mathematician Leonard Jimmie Savage happened across one of Bachelier’s works in a library and sent postcards to some friends asking if they’d ever heard of the French thinker. One of those cards went to Paul Samuelson, then a rising young economist who had published a popular textbook. Samuelson would draw on Bachelier’s 1900 study as he went on to become a key figure in developing the EMH.
In 1965, Samuelson published a paper “Proof That Properly Anticipated Prices Fluctuate Randomly,” sketching out the idea of market efficiency as a formal theory. That same year, University of Chicago economist Eugene Fama published his doctoral dissertation “The Behavior of Stock Market Prices,” which delved into market data to argue that equities are indeed an efficient market, which he defined as “a market where, given the available information, actual prices at every point in time represent very good estimates of intrinsic values.”