Risk Behavior and Performance Benchmarks in the Mutual Fund Industry

The determinants of risk tolerance play an essential role in asset pricing. In this paper, I develop and test empirically a behavioral model of investor risk strategies. Difficulty in quantifying many of the elements of behavioral theories has so far necessitated experimental, rather than empirical, evaluation of most such models. Therefore, the methodology employed in this paper – testing a behavioral theory on actual pricing data – represents a relatively new technique in behavioral finance. The context for my study is the U.S. mutual fund industry. This field offers an especially appropriate structure for the exploration of the concepts I develop, as well as exerting a key influence on market pricing. I base my model on concepts from the psychological decision making literature, adapting these theories to an investment context. Specifically, I explore fund managers’ risk choices relative to their distances from two reference points, Success (the target level of performance, usually identified as returns on a benchmark index) and Exit (the performance level below which a fund manager’s employment is terminated). I estimate this model on a large cross-sectional panel of 4,924 equity and 2,682 bond funds. My results support the hypothesis that managers underperforming relative to their reference points take larger risks in an attempt to attain their targets, while managers meeting or exceeding their targets limit risk to maintain their superior performance. Risk tolerance decreases as underperformers approach their reference points and increases as outperformers move even further ahead.