Abstract
Hedge funds databases are typically subject to high attrition rates because of fund termination and self-selection. Even when all funds are included up to their last available return, one cannot prevent that ex post conditioning biases affect standard estimates of performance persistence. In this paper we analyze the persistence in the performance of U.S. hedge funds taking into account look-ahead bias (multi-period sampling bias). To do so, we model attrition of hedge funds and analyze how it depends upon historical performance. Next, we use a weighting procedure that eliminates look-ahead bias in measures for performance persistence. The results show that the impact of look-ahead bias is quite severe, even though positive and negative survival-related biases are sometimes suggested to cancel out.
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