Performance persistence studies typically suffer from ex-post conditioning biases. As stressed by Carhart [Carhart, M.M., 1997. Mutual Fund Survivorship, Working Paper, Marshall School of Business, U.S.C.] and Carpenter and Lynch [J. Financ. Econ. 54 (1999) 337.], 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 look-ahead bias using weights based on probit regressions. First, we model how survival probabilities depend upon historical returns, fund age and aggregate economy-wide shocks, using two samples of US based ‘income’ and ‘growth’ funds. Subsequently, we employ a Monte Carlo study to analyze the size and shape of the look-ahead bias in performance persistence that arise when a survivorship free sample is used with standard techniques. In particular, we show that look-ahead bias induces a spurious U-shaped pattern in performance persistence. Finally, we demonstrate how a weighting procedure based upon probit regressions can be used to correct for this bias. In this way, we obtain look-ahead bias-corrected estimates of abnormal performance relative to a one-factor and the Carhart [J. Finan. 52 (1997) 57.] four-factor model, as well as its persistence. The results suggest that in this sample, look-ahead bias is of minor importance and does not seriously affect estimates of persistence. Our bias-corrected results closely correspond to the findings of Carhart [J. Finan. 52 (1997) 57.], implying that there is no evidence on a risk-adjusted basis for persistence in performance.

look-ahead bias, mutual funds, performance evaluation
Truncated and Censored Models (jel C34), Portfolio Choice; Investment Decisions (jel G11), Pension Funds; Other Private Financial Institutions (jel G23),
ERIM Top-Core Articles
Journal of Empirical Finance
Erasmus Research Institute of Management

ter Horst, J.R, Nijman, T.E, & Verbeek, M.J.C.M. (2001). Eliminating Look-Ahead Bias in Evaluating Persistence in Mutual Fund Performance. Journal of Empirical Finance, 8(4), 345–373. doi:10.1016/S0927-5398(01)00032-9