Prior Performance and Risk-Taking of Mutual Fund Managers: A Dynamic Bayesian Network Approach

Abstract

We analyze the behavior of mutual fund managers with a special focus on the impact of prior performance. In contrast to previous studies, we do not solely focus on the volatility as a measure of risk, but also consider alternative definitions of risk and style. Using a Dynamic Bayesian Network, we are able to capture non-linear effects and to assign exact probabilities to the mutual fund managers' adjustment of behavior. In contrast to theoretical predictions and some existing studies, we find that prior performance has a positive impact on the choice of the risk level, i.e., successful fund managers take more risk in the following calendar year. In particular, they increase the volatility, the beta and the tracking error and assign a higher proportion of their portfolio to value stocks, small firms and momentum stocks. Overall, poor performing fund managers switch to passive strategies.