Behavioral Finance and Your Portfolio. Michael M. Pompian
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Monday, October 18, 2004, a significant but mostly unnoticed article appeared in the Wall Street Journal. Eugene Fama, one of the leading scholars of the efficient market school of financial thought, was cited admitting that stock prices could become “somewhat irrational.”8 Imagine a renowned and rabid Boston Red Sox fan proposing that Fenway Park be renamed Mariano Rivera Stadium (after the outstanding New York Yankees pitcher), and you may begin to grasp the gravity of Fama's concession. The development raised eyebrows and pleased many behavioralists. (Fama's paper “Market Efficiency, Long-Term Returns, and Behavioral Finance” noting this concession at the Social Science Research Network is one of the most popular investment downloads on the web site.) The Journal article also featured remarks by Roger Ibbotson, founder of Ibbotson Associates: “There is a shift taking place,” Ibbotson observed. “People are recognizing that markets are less efficient than we thought.”9
As Meir Statman eloquently put it, “Standard finance is the body of knowledge built on the pillars of the arbitrage principles of Miller and Modigliani, the portfolio principles of Markowitz, the capital asset pricing theory of Sharpe, Lintner, and Black, and the option-pricing theory of Black, Scholes, and Merton.”10 Standard finance theory is designed to provide mathematically elegant explanations for financial questions that, when posed in real life, are often complicated by imprecise, inelegant conditions. The standard finance approach relies on a set of assumptions that oversimplify reality. For example, embedded within standard finance is the notion of Homo economicus, or rational economic man. It prescribes that humans make perfectly rational economic decisions at all times. Standard finance, basically, is built on rules about how investors “should” behave, rather than on principles describing how they actually behave. Behavioral finance attempts to identify and learn from the human psychological phenomena at work in financial markets and within individual investors. Standard finance grounds its assumptions in idealized financial behavior; behavioral finance grounds its assumptions in observed financial behavior.
Efficient Markets versus Irrational Markets
During the 1970s, the standard finance theory of market efficiency became the model of market behavior accepted by the majority of academics and a good number of professionals. The efficient market hypothesis had matured in the previous decade, stemming from the doctoral dissertation of Eugene Fama. Fama persuasively demonstrated that in a securities market populated by many well-informed investors, investments will be appropriately priced and will reflect all available information. There are three forms of the efficient market hypothesis:
1 The “Weak” form contends that all past market prices and data are fully reflected in securities prices; that is, technical analysis is of little or no value.
2 The “Semi-strong” form contends that all publicly available information is fully reflected in securities prices; that is, fundamental analysis is of no value.
3 The “Strong” form contends that all information is fully reflected in securities prices; that is, insider information is of no value.
If a market is efficient, then no amount of information or rigorous analysis can be expected to result in outperformance of a selected benchmark. An efficient market can basically be defined as a market wherein large numbers of rational investors act to maximize profits in the direction of individual securities. A key assumption is that relevant information is freely available to all participants. This competition among market participants results in a market wherein, at any given time, prices of individual investments reflect the total effects of all information, including information about events that have already happened, and events that the market expects to take place in the future. In sum, at any given time in an efficient market, the price of a security will match that security's intrinsic value.
At the center of this market efficiency debate are the actual portfolio managers who manage investments. Some of these managers are fervently passive, believing that the market is too efficient to “beat”; some are active managers, believing that the right strategies can consistently generate alpha (alpha is performance above a selected benchmark). In reality, active managers have a hard time beating their benchmarks. This may explain why the popularity of exchange-traded funds (ETFs) has exploded and why venture capitalists are now supporting new ETF companies, many of which are offering a variation on the basic ETF theme.
The implications of the efficient market hypothesis are far-reaching. Most individuals who trade stocks and bonds do so under the assumption that the securities they are buying (selling) are worth more (less) than the prices that they are paying. If markets are truly efficient and current prices fully reflect all pertinent information, then trading securities in an attempt to surpass a benchmark is a game of luck, not skill.
The market efficiency debate has inspired literally thousands of studies attempting to determine whether specific markets are in fact “efficient.” Many studies do indeed point to evidence that supports the efficient market hypothesis. Researchers have documented numerous, persistent anomalies, however, that contradict the efficient market hypothesis. There are three main types of market anomalies: Fundamental Anomalies, Technical Anomalies, and Calendar Anomalies.
Fundamental Anomalies
Irregularities that emerge when a stock's performance is considered in light of a fundamental assessment of the stock's value are known as fundamental anomalies. Many people, for example, are unaware that value investing—one of the most popular and effective investment methods—is based on fundamental anomalies in the efficient market hypothesis. There is a large body of evidence documenting that investors consistently overestimate the prospects of growth companies and underestimate the value of out-of-favor companies.
One example concerns stocks with low price-to-book-value (P/B) ratios. Eugene Fama and Kenneth French performed a study of low price-to-book-value ratios that covered the period between 1963 and 1990.11 The study considered all equities listed on the New York Stock Exchange (NYSE), the American Stock Exchange (AMEX), and the Nasdaq. The stocks were divided into 10 groups by book/market and were reranked annually. The lowest book/market stocks outperformed the highest book/market stocks 21.4 percent to 8 percent, with each decile performing more poorly than the previously ranked, higher-ratio decile. Fama and French also ranked the deciles by beta and found that the value stocks posed lower risk and that the growth stocks had the highest risk. Another famous value investor, David Dreman, found that for the 25-year period ending in 1994, the lowest 20 percent P/B stocks (quarterly adjustments) significantly outperformed the market; the market, in turn, outperformed the 20 percent highest P/B of the largest 1,500 stocks on Compustat.12
Securities with low price-to-sales ratios also often exhibit performance that is fundamentally anomalous. Numerous studies have shown that low P/B is a consistent predictor of future value. In What Works on Wall Street, however, James P. O'Shaughnessy demonstrated that stocks with low price-to-sales ratios outperform markets in general and also outperform stocks with high price-to-sales ratios. He believes that the price/sales ratio is the strongest single determinant of excess return.13
Low price-to-earnings ratio (P/E) is another attribute that tends to anomalously correlate with outperformance. Numerous studies, including David Dreman's work, have shown that low P/E stocks tend to outperform both high P/E stocks and the market in general.14
Ample evidence also indicates that stocks with high dividend yields tend to outperform others. The Dow Dividend Strategy counsels purchasing the 10 highest-yielding Dow stocks.