In financial studies and analyses, one of the great debates is whether or not the market is efficient. That is, whether market prices reflect all relevant information and whether or not an investor can continually “beat the market.” In Eugene Fama’s 1970 work on Efficient Capital Markets, he writes “a market in which … firms can choose among securities that represent ownership of firms’ activities under the assumption that security prices at any time “fully reflect” all available information … is called efficient.”
Weak form efficiency focuses primarily on historical prices, and how past data, charts, and pricing information alone cannot be used to determine current security prices. Semi-strong form is the most well-known form as it is the basis behind most market efficiency research. Semi-strong form tests whether the market is efficient based on past information and also, current public information like press releases, announcements, or annual reports. Finally, strong form efficiency extends this concept to include all information — public and private. Even given insider or privy information, the efficient market theory should stand under strong form, with a few exceptions.
Efficient market theory (EMT) mathematical models show that an efficient market does not render all stock prices and values equal at every point in time. The EMT says any deviations between price and value are random, and it is equally likely that an investor will suffer a loss as it is for him to earn a gain.
But what about all of the reported anomalies? The January effect, low P/E ratios, and the small firm effect should not hold under the efficient market theory. The EMT says anomalies are possible, but such cases should be random and unbiased in nature. For this reason, among others, many argue the validity of the EMT.
Should you assume an efficient market? The consensus seems to be that the EMT has many practical applications, and has been the framework for a plethora of additional research, but the EMT does not completely describe the market as a whole. If stocks truly take random walks, could anyone ever earn any money?
1. The Human Factor
Phillip Russel, assistant professor at the University of Philadelphia, enters behavior into the equation. He writes that, “Critics of EMH argue that the predictability of stock returns reflects the psychological factors, social movements, noise trading, and fashions or “fads” of irrational investors in a speculative market. The question about whether predictability of returns represents rational variations in expected returns or arises due to irrational speculative deviations from theoretical values has provided the impetus for fervent intellectual inquiries in the recent years.”
Russel goes on to explain the arguments of Shleifer and Summers, who posit there are two types of investors — rational observers and arbitrageurs who trade based on the information they survey, and also “noise traders” who act on perceived trends, hearsay, and overreact to good or bad news. Noise traders cause prices to fluctuate away from equilibrium values and rational investors provide needed balance, stabilizing prices back towards equilibrium. If you think of the market like a human body, you can think of the rational investor or arbitrageur as an antibody. When an antigen enters the body, antibodies go to work to get your system back into proper harmony. Even given an efficient market, different types of investors respond to information differently. The nature in which a noise trader responds is an exploitable piece of knowledge.
2. Data Anomalies
Under the EMT, the random nature of anomalies should render such occurrences temporary. Within a relatively short time period, prices should return to their value. Mathematically, most would say there is no such thing as true randomness and you can almost always find a theme or pattern within a set of data.
This is not to say an investor can consistently (or even inconsistently) earn money by investing in reversals or neglected stocks, for instance. However, technical analysis of data (e.g. directional movement indicators) can sometimes accurately indicate future movement, even given a market that is thought to be efficient.
In a New York University publication, Donald Byrne writes that, “In an efficient market, a strategy of randomly diversifying across stocks or indexing to the market, carrying little or no information cost and minimal execution costs, would be superior to any other strategy, that created larger information and execution costs.”
The majority of risk you face is unsystematic, or diversifiable risk. Therefore, diversification is perhaps an effective manner in which to see some sort of gain in an efficient market, where gains and losses are equally likely.
The EMT has opened our eyes to various different views. From Keynes, who viewed investors more as speculators with more short-run motives, to Rozeff and Kinney, who were the first to document higher than average returns in January. The EMT will likely continue to be a framework upon which research builds. In the future, as technology results in the near-instant sending and receiving of information, the market may just become completely efficient.