An Empirical Evaluation of Hedge Fund Managerial Skills Using Bayesian Techniques

Abstract

This paper makes use of the Bayesian method to evaluate hedge fund managers’ selectivity, market timing and outperformance skills separately, and investigates their persistence from January 1995 to June 2010. We divide this sample period into four overlapping sub-sample periods that contain different economic cycles. We define a skilled manager as a manager who can outperform the market in two consecutive sub-sample periods. We employ Bayesian linear CAPM and Bayesian quadratic CAPM to generate skill coefficients during each sub-sample period. We found that fund managers who possess selectivity skills can outperform the market at 7.5% significant level if and only if the economic conditions that governed the financial market during the period between sub-sample period2 and sub-sample period3 remain the same.