Survival, Look-Ahead Bias, and Persistence in Hedge Fund Performance

Abstract

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 look-ahead bias in measures for performance persistence. In contrast to earlier results for mutual funds, the impact of look-ahead bias is exacerbated for hedge funds due to their greater level of total risk. At the four quarter horizon, look-ahead bias can be as large as 3.8%, depending upon the decile of the distribution. At the quarterly level, we …nd positive persistence in hedge fund returns, also after correcting for investment style. The empirical pattern at the annual level is also consistent with positive persistence, but its statistical signi…cance is weak.

Factors that affect the performance of distressed securities hedge funds

“…Table 6 illustrates the results. As documented by previous literature (for example, Liang, 2000;Brown et al, 2001;Baquero et al, 2005;Malkiel and Saha, 2005;Liang and Park, 2010), we find that fund returns, risk and high-water mark play an important role in the explanation of fund survival. Fund return has a statistically significant positive influence on fund survival.…”

“…Many authors have analyzed the survival behavior of hedge funds in recent years (see, among others, Liang, 2000;Brown et al, 2001;Baquero et al, 2005;Malkiel and Saha, 2005;Liang and Park, 2010). These studies differ with respect to the proposed methodology for modeling the liquidation process and with respect to the included variables.…”

“…These studies differ with respect to the proposed methodology for modeling the liquidation process and with respect to the included variables. While Liang (2000), Baquero et al (2005) and Malkiel and Saha (2005) use probit analysis, Brown et al (2001) and Liang and Park (2010) use both Cox (1972) proportional hazard models and discrete-time binary choice models (logit and probit models). As we will discuss below, we use a parametric logit model to analyze the effects of fund-specific characteristics on fund survival, but also implement various other approaches for the sake of robustness.…”

Chasing performance persistence of hedge funds – Comparative analysis of evaluation techniques

“…Controlling for look-ahead bias, Baquero et al 6 find a clear pattern of persistence in raw returns of hedge funds at the quarterly horizon but no statistically significant persistence at the annual horizon. Based on style-adjusted returns, the results show (on average) outperformance for top-decile funds of the preceding selection period at both the quarterly and annual horizons, though not significantly in the statistical sense.…”

Look-Ahead Benchmark Bias in Portfolio Performance Evaluation

“…ter Horst et al (2001) introduce a weighting procedure based upon probit regressions which models how survival probabilities depend upon historical returns, fund age and aggregate economy-wide shocks, and which provides look-ahead bias-corrected estimates of mutual fund performances. Baquero et al (2005) apply the methodology of ter Horst et al (2001) to hedge-fund performance, which requires a well-specified model that explains survival of hedge funds and how it depends upon historical performance. ter Horst and Verbeek (2007) extend the look-ahead bias correction method of Baquero et al (2005) to hedge-funds by correcting separately for additional self-selection biases that plague hedge-fund databases (underperformers do not wish to make their performance known while funds that performed well have less incentive to report to data vendors to attract potential investors).…”