Behavioral Portfolio Management. C. Thomas Howard
it is necessary to go beyond what a majority of investors believe and examine what stock price data tell us regarding the importance of emotions in the price discovery process.
There is considerable evidence that stock prices are driven by something other than fundamentals and that emotions play a major role. I now discuss what I believe are the two most germane research streams. The first stream deals with excess stock market volatility. Robert Shiller of Yale – 2013 Nobel laureate – highlighted excess volatility in 1981 and since then it has been hotly debated. But after 30 years of empirical efforts to explain excess volatility and thus resurrect the Efficient Markets Hypothesis, Shiller stands by his initial assertion:
“After all the efforts to defend the efficient markets theory there is still every reason to think that, while markets are not totally crazy, they contain quite substantial noise, so substantial that it dominates the movements in the aggregate market. The efficient markets model, for the aggregate stock market, has still never been supported by any study effectively linking stock market fluctuations with subsequent fundamentals.” [3]
The fact that noise, rather than fundamentals, dominates market price movements is clear evidence that Crowds dominate stock pricing.
The Equity Premium Puzzle research stream provides additional evidence that emotions play a prominent role. The long-term equity risk premium should be associated with long-term fundamental risks. Rajnish Mehra of the University of California, Santa Barbara and 2004 Nobel laureate Edward Prescott of Arizona State University report that the US stock market has generated a risk premium averaging around 7% annually from the 1870s to the present. They argue that this premium is too large, by a factor of two or three, relative to fundamental market risk, so they coined the term Equity Premium Puzzle. [4] Over the last 25 years, there have been numerous attempts to find a fundamental explanation of this puzzle, but with little success.
However, Shlomo Benartzi of UCLA and Richard Thaler of the University of Chicago provide an emotional explanation:
“The equity premium puzzle refers to the empirical fact that stocks have outperformed bonds over the last century by a surprisingly large margin. We offer a new explanation based on two behavioral concepts. First, investors are assumed to be “loss averse,” meaning that they are distinctly more sensitive to losses than to gains. Second, even long-term investors are assumed to evaluate their portfolios frequently. We dub this combination “myopic loss aversion.” Using simulations, we find that the size of the equity premium is consistent with the previously estimated parameters of prospect theory if investors evaluate their portfolios annually.” [5]
The observed 7% equity premium is thus the result of short-term loss aversion and the investor ritual of evaluating portfolio performance annually, rather than the result of fundamental risk. Putting these two results together leads to the conclusion that both stock market volatility and long-term returns are largely determined by investor emotions.
Beyond these two emotion-driven results, numerous other pricing distortions have been uncovered. Many of these have been linked to the decision errors documented in the behavioral science literature. David Hirshleifer of the University of California, Irvine provides three organizing principles to place the price distortion phenomena into a systematic structure:
1 People rely on heuristics because people face cognitive limitations. Owing to a shared evolutionary history, people might be predisposed to rely on the same heuristics and therefore be subject to the same biases (read Emotional Crowds).
2 People inadvertently signal their inner states to others. This means that nature might have selected for traits such as overconfidence in order that people signal strong confidence to others.
3 People’s judgments and decisions are subject to their own emotions as well as to their reason.
Santa Clara University’s Hersh Shefrin, in Behavioralizing Finance, provides an excellent summary of four behavioral finance studies, including David Hirshleifer, mentioned above, along with Nicholas Barberis of Yale University and Richard Thaler; Malcolm Baker of Harvard, Richard Ruback of Harvard, and Jeffrey Wurgler of NYU; and Avanidhar Subrahmanyam of UCLA. He also presents a comprehensive list of behavioral finance articles.
The ineffectiveness of arbitrage
A key difference between BPM and MPT is the extent to which arbitrage is effective in eliminating stock price distortions. Research over the last 40 years has shown that arbitrage has not been able to eliminate such distortions, termed anomalies since they are inconsistent with Efficient Market predictions. There are three possible reasons for this lack of effectiveness:
1 the difficulty in identifying arbitrage opportunities,
2 arbitrage is costly and risky, or
3 there are few if any market participants willing to engage in arbitrage.
Clearly stocks are difficult to value and so there is validity to the first reason. But even when the price distortion can be accurately estimated, such as with closed-end funds, the distortions persist. Cost and risk clearly make arbitrage difficult, but one would think that there is sufficient incentive to attract a large number of arbitragers into the stock market.
However, recent results by Bradford Cornell of the California Institute of Technology, and Wayne Landsman and Stephen Stubben, both of the University of North Carolina, are discouraging in this regard. They find a tendency for both mutual funds and sell-side analysts to exacerbate sentiment-driven price movements, rather than dampen them as one would expect of supposedly rational investors. That is, institutional professionals tend to join the Emotional Crowds rather than act as BDIs.
David McLean of MIT and Jeffrey Pontiff of Boston College explore the limits when arbitraging academically-identified anomalies. Starting with a sample of 82 such anomalies, they find that two-thirds of resulting excess returns remain even five years after publication. Furthermore, they find that the effectiveness of arbitrage has not improved in recent years, even with steep declines in transaction costs and the greater dominance of supposedly rational institutional investors.
Indeed, emotion trumps arbitrage.
Finally, Hersh Shefrin’s insightful observation is of interest:
“Finance is in the midst of a paradigm shift, from a neoclassical based framework to a psychologically based framework. Behavioral finance is the application of psychology to financial decision making and financial markets. Behavioralizing finance is the process of replacing neoclassical assumptions with behavioral counterparts. … the future of finance will combine realistic assumptions from behavioral finance and rigorous analysis from neoclassical finance.” [6]
Thus Basic Principle I, that Emotional Crowds dominate pricing, is a logical first step in building an effective decision process for investing.
Basic Principle II: Behavioral data investors earn superior returns
Basic Principle I would seem to open the door for BDIs to earn superior returns by taking positions opposite the Crowd. This is not necessarily the case, since even though there is little doubt emotions increase volatility, the resulting distortions might be random and unpredictable, making it difficult if not impossible to take advantage of them. So beyond the fact that emotions drive prices, it is necessary to show that the resulting distortions are measurable and persistent.
The behavioral finance literature is full of examples of measurable stock price distortions. [7] It would therefore seem easy to build superior performing portfolios, but in order to do so means taking positions that are different from the Crowd. The powerful need for social validation acts as a strong deterrent for many investors, discouraging them from pursuing such an approach. It is tough to leave the Emotional Crowd and become a BDI. Thus price distortions are measurable and persistent, but building a portfolio benefiting from these distortions is emotionally difficult.
In order to demonstrate that it is possible to earn superior returns, I turn to active equity mutual fund research.