In the last few decades, academics and practitioners have studied, defined and begun to exploit anomalies arising from human nature. The result is a burgeoning field known as behavioral economics, which traces its roots as far back as Adam Smith and studies the convergence of traditional economic theory and psychology. It appears that the confluence of certain social, cognitive and emotional factors can provide significant, and perhaps superior, explanatory power as it relates to financial modeling.
While the efficient market hypothesis makes a lot of sense in a world where investors act in a rational and predictable fashion, what happens when these assumptions don’t hold and markets confound even the most seasoned investment professionals? Enter the role of behavioral biases that might better explain the actions of security prices and financial markets.
Madison Avenue and Wall Street have thrived by taking advantage of the fact that we act irrationally, have difficulty with self-control and, in general, are selfish. There are limits to our cognitive abilities that result in decision-making processes that often involve shortcuts or rules of thumb, and we are influenced by our culture and individual circumstances. In short, we are emotional beings.
If we are so unpredictable, how can something like behavioral economics provide investors with an advantage? The key lies in identifying consistent patterns of behavior that not only are scientifically proven, but also make common sense. Daniel Kahneman and Amos Tversky are considered pioneers in behavioral economics, and some of their early research illustrates how our behavior can lead to exploitable opportunities.
For example, mean reversion is often utilized as an investment strategy for determining whether stocks are over- or undervalued and should thereby be purchased or sold. So why should a mean reversion strategy work if markets are, indeed, efficient? A likely explanation lies in behavioral biases, including the availability heuristic, aversion to losses and anchoring.
The availability heuristic has many features, but basically refers to solving problems via mental shortcuts. The consequence of this bias is that new information is given too much weight when making decisions because of the cognitive ease with which it can be recalled. This explains why stock prices are predisposed to overreaction; investors overweight new data, such as unfavorable news events, while ignoring potentially more pertinent information that is less cognitively available. After the initial overreaction to a negative news event occurs, investors who still hold the stock become loss averse, unwilling to sell their position. Conversely, other investors who were anchored to an initial price view the new lower price as a bargain. This is one reason why portfolio managers periodically increase their exposure to underperforming positions and trim their exposure to outperforming positions. As all investors finish digesting the new information, prices revert from the extremes, causing a previously underperforming stock to outperform and vice versa.
So how does this growing body of knowledge translate into something actionable? The prerequisite for true alpha generation (which is rare) is an understanding of what market inefficiencies exist, why they exist and why they should reasonably persist. Insight into the driving factors behind investor behavior, if less than rational, provides the answers to these questions and presents the opportunity to exploit the resulting inefficiencies.
While investment strategies of all types can benefit from being grounded in such an approach, freeing up the long-only constraint allows investors to more fully exploit both the fear and greed manifested in security prices.
Strategies such as long-short equity, long-short credit or managed futures, for example, have more tools to express their views, which increase the number of “at bats,” if you will. This is important because, as Grinold’s law of active management is often interpreted, value add is a function of skill times the number of decisions made or bets taken.
In an increasingly complex world, complexity itself provides the opportunity for those equipped to face it, and knowing why market participants act as they do is more than half the battle.