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...

A wide range of empirical biases hampers hedge fund databases. In this paper we focus upon survival-related biases and disentangle look-ahead biases due to self-selection of funds and due to fund termination. Self-selection arises because funds voluntarily report their information to data...

We analyze the performance persistence in hedge funds taking into account look-ahead bias (multi-period sampling bias). We model liquidation of hedge funds by analyzing how it depends upon historical performance. Next, we use a weighting procedure that eliminates look-ahead bias in measures for...

This paper analyzes the properties of a number of estimators that can be used to estimate short-run persistence in mutual fund returns. When data for different funds are pooled, it is advisable to correct for cross-sectional differences in expected returns. However, these adjustments may induce...

Performance persistence studies typically suffer from ex-post conditioning biases. As stressed by Carhart (1997a) and Carpenter and Lynch (1999), standard methods of analysis on a survivorship free sample are subject to look-ahead biases. In this paper, we show how one can easily correct for...

In this paper we analyze the persistence in the performance of hedge funds taking into account look-ahead bias (multi-period sampling bias). To do so, we model liquidation of hedge funds and analyze how it depends upon historical performance. Next, we use a weighting procedure that eliminates...

We analyze the performance persistence in hedge funds taking into account look-ahead bias (multi-period sampling bias). We model liquidation of hedge funds by analyzing how it depends upon historical performance. Next, we use a weighting procedure that eliminates look-ahead bias in measures for...