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 a.ect 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. At
horizons of one and four quarters, we find clear evidence of positive
persistence in hedge fund returns, also after correcting for
investment style. At the two-year horizon, past winning funds tend to
perform poorly in the future