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Testing Theories of Investor Behavior Using Brain Imaging
Ventrmedial Prefrontal Cortex Encodes Net Capital Gain
Achievement/Results
Like many other forms of human decision-making, investor behavior is characterized by numerous irrational and suboptimal behaviors, which are responsible for large financial inefficiencies. The recent collapse of the real estate bubble is a dramatic reminder of the profound economic consequences such ‘irrational exuberances’ can have. IGERT trainee Cary Frydman, in collaboration with IGERT faculty Colin Camerer, Peter Bossaerts, and Antonio Rangel, are among the first researchers to show that measures of neural activity provided by functional magnetic resonance imaging (fMRI) can be used to test theories of suboptimal investor behavior. To do so, they developed a novel experimental framework in which subjects traded stocks in an experimental market while they measured their brain activity. Behaviorally, they found that their average subject exhibited a strong disposition effect in his trading.
The disposition effect is a well known example of suboptimal investor behavior: investors tend to sell more stocks that have gone in up value than stocks that have gone down in value, leading to lower average profits. By probing neural activity during trading, they were able to test a specific theory of the disposition effect: the “realization utility” hypothesis, which argues that the effect arises because people derive utility directly from the act of realizing gains and losses. In other words, people sell winning stocks too early because the act of selling such stocks is pleasurable. In support of this hypothesis, they found that activity in an area of the brain known to encode the value of decisions correlates with the capital gains of potential trades, that the size of these neural signals correlates across subjects with the strength of the behavioral disposition effects, and that activity in an area of the brain known to encode experienced utility exhibits a sharp upward spike in activity at precisely the moment at which a subject issues a command to sell a stock at a gain. These insights provide important new insights into the processes and mechanisms underlying suboptimal investor behavior and may ultimately lead to better investor decision-making.
Address Goals
Finance has long struggled with the fact that it is difficult to adjudicate among theories of investor behavior using behavioral data alone. The reason for this is that many competing theories are behaviorally equivalent (they make the same behavioral predictions). This research represents an important milestone in finance research. By integrating experimental finance methods and cognitive neuroscience, this research is among the very first to add neurobiological constraints to finance. Since neurobiological data can distinguish among behaviorally-equivalent theories, this research represents an important methodological innovation that will shed fundamental new light on investor behavior and provide a basis for developing both improved individual decision-making and ultimately policy and regulatory reform.
In addition, this research represents the interdisciplinary training of a new generation of economists trained both in traditional economics and finance and cognitive neuroscience. As IGERT trainee Cary Frydman moves into an assistant professor position in the fall of 2012, the new interdisciplinary model of finance will expand to prepare the next generation of economists, who will integrate economics and neuroscience. Just as interdisciplinary training has profoundly transformed much of psychology into cognitive neuroscience, a new interdisciplinary economics and neuroscience workforce will be better positioned to both understand and solve the complex interplay between financial systems and human decision-making. This promises not only to improve such decision-making, but make the country more competitive and able to better avoid the large economic fluctuations that stem from this interplay and their large economic and human costs.
