overall economy to divineThe efficient market hypothesis is a model for how markets perform. A market is said to be efficient if prices in that market reflect all available information.

Suppose you hear a firm has just announced quarterly earnings that exceed analysts’ expectations. You rush to buy the stock but find its price has already risen two dollars from yesterday’s close. Are you too late? Might the price continue to rise on the positive news, or has the market overreacted? Perhaps you should sell short instead? The efficient market hypothesis says these questions are mute—that whatever information you consider in making a decision has already been incorporated into stock prices and is useless for predicting future prices. Market efficiency renders speculative trading pointless.

The related random walk hypothesis of the early 1960s was an empirical result. Based on time-series analyses of past stock prices, researchers concluded that the prices behaved like geometric random walks. This threw cold water on the practice of technical analysis—the study of stock price charts to divine future price movements. It did not, however, rule out fundamental analysis—the study of a company’s business, its market and/or the overall economy—as a means of predicting future price movements. Developed by Eugene Fama in the late 1960s and early 1970s, the efficient market hypothesis went beyond the random walk hypothesis to reject both technical analysis and fundamental analysis.

Origins of the Efficient Market Hypothesis

Fama’s background gave him direct experience with the lessons of the random walk hypothesis. He had helped pay his way through college by working for professor Harry Ernst, who published a newsletter recommending stock picks based on technical analysis. Ernst gave Fama the job of studying past prices to identify profitable trading systems. Identifying systems that performed well on the historical data was easy, but those systems routinely failed when used to trade with real money. Fama was learning for himself what is widely known to professional investors—that data mining can produce all sorts of trading systems that work beautifully on the data from which they are derived but are worthless otherwise.

Fama took these experiences with him to the University of Chicago, where he earned a Ph.D. in finance. His thesis was published in the Journal of Business in 1965 as the “Behavior of stock market prices.” This elaborated on the random walk hypothesis, fleshing out other researchers’ justification for why prices should follow a random walk. It reported on Fama’s own empirical studies of past price data. Advances in computers had made it possible for him to perform more elaborate studies than earlier researchers. Fama also looked at flaws in the random walk hypothesis, focusing especially on the issue of market leptokurtosis. But his overall conclusions were dismal for market technicians. The random walk hypothesis was an excellent model for the markets, and whatever flaws it might have weren’t anything that would present market technicians with trading opportunities.

Although Fama’s paper was about the random walk hypothesis, it is notable for introducing the term “efficient market” and anticipating his efficient market hypothesis: [1]

… a situation where successive price changes are independent is consistent with the existence of an “efficient” market for securities, that is, a market where, given the available information, actual prices at every point in time represent very good estimates of intrinsic values …

In an abbreviated version of his paper, which Fama (1965) wrote for the practitioner-oriented Financial Analysts Journal, he elaborated:[2]

An “efficient” market is defined as a market where there are large numbers of rational, profit-maximizers actively competing, with each trying to predict future market values of individual securities, and where important current information is almost freely available to all participants … on the average, competition will cause the full effects of new information on intrinsic values to be reflected “instantaneously” in actual prices.

But he still held out hope for fundamental analysts:[3]

… the existence of many sophisticated analysts helps make the market more efficient which in turn implies a market which conforms more closely to the random walk model. Although the returns to these sophisticated analysts may be quite high, they establish a market in which fundamental analysis is a fairly useless procedure both for the average analyst and the average investor.

This was just so much theory, unsupported by empirical facts. Fama’s empirical work had exclusively looked at time series of prices, and a study of fundamental analysis would likely need to look at investment managers’ performance or study security price movements following announcements, such as stock splits or earnings announcements. In 1965, the scant research along such lines—Cowles (1933), Friend et al. (1962) and Horowitz (1963) studying investment managers’ performance—had found no evidence of sophisticated analysts earning “quite high” returns.

Between 1965 and 1970, many empirical studies were performed on stock price behavior or investment managers’ performance. These culminated in 1970 with Fama’s second landmark paper, which appeared in the Journal of Finance and was titled “Efficient capital markets: A review of theory and empirical work.” In it, Fama elaborated on his theory of efficient markets and reviewed the developing literature. Based on the terminology of his colleague Harry Roberts, he reported on empirical tests for three different levels of market efficiency:

  • A market has weak efficiency if prices fully reflect any information contained in past price data. Weak efficiency rejects technical analysis. It is essentially the random walk hypothesis but without as full a characterization of the stochastic process that describes price behavior.
  • A market has semi-strong efficiency if prices fully reflect all readily-available public information—past prices, economic news, earnings reports, etc. Tests of semi-strong efficiency are those that study stock price movements following announcements, such as stock splits or earnings announcements.
  • A market has strong efficiency if prices fully reflect all public and privileged information. Privileged information includes knowledge available to a market maker, insider information available to corporate managers, or information that investment managers spend time and money to compile for their own use.

Empirical Studies of the Efficient Market Hypothesis

Because weak market efficiency overlaps with the random walk hypothesis, empirical testing of the efficient market hypothesis focuses on semi-strong or strong market efficiency. Early tests of these relied on the then-new capital asset pricing model of Sharpe (1964) and Lintner (1965). For semi-strong efficiency, this allowed researchers to disaggregate individual security’s returns into a component due to broad market moves and a “residual” component specific to each security. Semi-strong efficiency was tested by assessing the behavior of those residuals leading up to and following announcements. Fama, Fisher, Jensen and Roll (1969) performed such a study around announced stock splits. Ball and Brown (1968) did so with quarterly earnings announcements. Scholes (1969) considered new stock issuances as well as large underwritten sales of existing common stock. All these studies strongly supported semi-strong market efficiency.

Fama acknowledged that strong market efficiency could not be an entirely realistic model for the markets, since certain non-public information clearly presented a profit opportunity for those who possessed it. Market makers on the New York Stock Exchange made consistent profits trading stocks due to the privileged information their positions afforded them. Corporate managers could profit from trading based on inside information their positions made available to them (although the practice was and still is illegal in the United States). For Fama, the question was not whether the markets were strongly efficient. It was, rather, to what degree are they strongly efficient? Specifically, how far down through the investment community do deviations from strong market efficiency permeate? Does it pay for the average investor to expend resources searching out little known information? Can market professionals profit from such activities? More generally, who in the investment community possesses “special information” they can profit from?

Mutual Funds and the Efficient Market Hypothesis

Much early research contributing to the efficient market hypothesis focused on the performance of mutual fund managers. If they were able to consistently outperform the markets, this would suggest they possessed useful insights or information. CAPM provided a framework for considering their performance on a risk-adjusted basis. This was important because managers could boost their absolute returns by merely increasing the systematic risk (beta) of their portfolio—which had nothing to do with their ability to time the market or pick stocks. Various metrics for a manager’s risk-adjusted performance were proposed, including the Treynor ratio (1965), Sharpe ratio (1966) and Jensen’s alpha (1968). Fama cited all three papers, but he focused on Jensen’s study of mutual funds’ alphas.

Jensen gathered annual return data for the S&P 500 (which he used as a proxy for the market portfolio) and 115 mutual funds. He used fund returns after fees but ignoring any sales loads. He had complete data for 1955-1964, but some funds had data going back as far as 1945, which he used as well. He performed a regression for each mutual fund to determine its alpha. His estimated alphas for all 115 mutual funds are summarized in Exhibit 1, which is reproduced from his paper.

Exhibit 3: A frequency distribution of the alphas Jensen estimated for 115 mutual funds based on at least ten years of data for each. The vast majority have estimated alphas that are less than zero. The average fund's alpha was –.011, (that is –1.1%). Results are after fees but not including sales loads. Returns, and hence alphas, are with continuous compounding. Reproduced from Jensen (1968).

Exhibit 1: A frequency distribution of the alphas Jensen estimated for 115 mutual funds based on at least ten years of data for each. The vast majority have estimated alphas that are less than zero. The average fund’s alpha was –.011, (that is –1.1%). Results are after fees but not including sales loads. Returns, and hence alphas, are with continuous compounding. Reproduced from Jensen (1968).

The vast majority of the funds had negative estimated alphas, with the average being negative 1.1%. This means that, after fees, but not including sales loads, the average fund underperformed the overall market by 110 basis points a year. Looking at fund returns before fees, the results were only marginally better. Then a majority still had negative estimated alphas, but with the average being negative 0.4%. Jensen noted[4]

An examination [of the data] … reveals only 3 funds which have performance measures which are significantly positive at the 5% level. But before concluding that these funds are superior we should remember that even if all 115 of these funds had a true α equal to zero, we would expect (merely because of random chance) to find 5% of them or about 5 or 6 funds … at the 5% level.

Exploitable Violations of the Efficient Market Hypothesis

Fama’s efficient market hypothesis has been an extremely influential theory. Investors are well advised to accept it unequivocally because violations that are significant enough to afford trading opportunities are 1) rare, 2) likely illegal, and 3) if not illegal, unlikely to be advertised to the retail or institutional investing public, anyway. One of the oldest questions to plague Wall Street brokers is: if their investment ideas (technical analysis, stock tips, buy-write programs, etc.) are so good, why do brokers give the ideas away rather than invest their own money in them?

But violations of strong or semi-strong efficiency have been documented. There is even a literature on market anomalies, documenting violations of weak efficiency, although these generally are too minor to afford profit opportunities after transaction costs.

Jones and Litzenberger (1970) published one of the first significant violations of semi-strong efficiency. Suspecting that the markets respond slowly to unexpectedly good earnings announcements, they constructed portfolios of stocks that had recently announced such earnings and found that the portfolios outperformed the overall market in subsequent months. The phenomenon was observable in every one of ten overlapping periods they considered between 1964 and 1967, and it was significant enough to earn excess returns after transaction costs.

Financial institutions have also identified a few violations of semi-strong efficiency over the years. Not surprisingly, they didn’t give these gems away to clients. The firms kept quiet and reaped profits for themselves. One such opportunity was pairs trading, which Morgan Stanley exploited in the 1980s. Another was fixed income arbitrage, which Salomon Brothers had a team of professionals exploit a decade later. Such violations don’t last, since traders soon exploit the opportunities out of existence. Don’t try pairs trading. The technique is so widely known today that there are books on the subject. I doubt anyone has made a dime from it in the last ten years. As for fixed income arbitrage, the Salomon team set up their own hedge fund, Long-Term Capital Management (LTCM), in the early 1990s. But by then, other hedge funds and brokers were also getting involved in fixed income arbitrage. Profits were tight and LTCM dabbled in other, unproven speculative trading strategies. Market turmoil, combined with the fund’s leverage, inflicted massive losses, and LTCM failed in 1998.

Today’s boom in hedge funds in not a violation of the efficient market hypothesis. There is no evidence that hedge funds consistently outperform the market. There is tremendous hype over unsubstantiated claims and flawed industry studies that purport that they have. The studies are based on incomplete performance data compiled in ways that are known to introduce biases. If nothing else, the efficient market hypothesis has demonstrated how rare it is to consistently outperform the markets, so there is something peculiar about the thousands of hedge funds being started up each year—each year taking the place of other thousands of hedge funds that are quietly shut down without any public explanation. Brokers and hedge fund managers are getting rich off the hedge fund boom, but investors are not.

Influence of the Efficient Market Hypothesis

The efficient market hypothesis has never been much of a match for the marketing machine of Wall Street. Still, it has had more influence than most academic theories. In 1971, Wells Fargo Bank established the first indexed portfolio for a single pension fund client. More passively-managed portfolios, and even indexed mutual funds, soon followed. Such funds generally have no loads, low fees and, because they hold the securities comprising specific equity indexes, minimal transaction costs. Their custody fees are often lower as well. Today, many billions of dollars are invested in index funds that routinely outperform comparable actively-managed funds.

The efficient market hypothesis is kept before the public with Burton Malkiel’s popular book A Random Walk Down Wall Street. The engrossing book targets individual investors, but its insightful discussions of the random walk hypothesis, efficient market hypothesis and portfolio theory have educated entry-level professionals since the book was first released in 1973. Any professional involved in trading or investing who has not read it should consider himself culturally illiterate.


  • [1] Fama (1965a), p. 34.
  • [2] Fama (1965b), p. 56.
  • [3] Fama (1965b), p. 58.
  • [4] Jensen (1968), p. 410.


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