The Conditional Performance of Indian Mutual Funds: An Empirical Study

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One of the most important developments in the field of finance during last forty years is the mutual fund performance evaluation technique. The traditional techniques use the unconditional moments of the returns. Such techniques cannot capture the time-varying element of expected return. As a consequence Ferson and Schadt (96) advocate a technique called conditional performance evaluation, designed to address this problem. This paper utilizes that technique on a sample of 89 Indian mutual fund schemes, over the period of 1999:1 to 2003:7. The broad based S&P CNX 500 is used in the study as benchmark. The study uses the lagged information variables - T-bill yield, dividend yields, term structure yield spread and a dummy for April-effect. The paper measures the performance with both unconditional and conditional form of - CAPM, Treynor-Mazuy model and Henriksson-Merton model. We examine the effect of incorporating lagged information variables into the evaluation of mutual fund managers' performance in Indian context. The result suggests that the use of conditioning lagged information variables improves the performance of the mutual fund schemes, causing the alphas to shift towards the right and reducing the number of negative timing coefficients. Tech rally of 1999 to 2001 is a major event in the history of Indian capital market. We have also incorporated the impact of the tech rally in the conditional models by introducing a dummy variable indicating the period of rally in tech stocks. We found that fund managers' performance as well as timing skill worsens with the inclusion of this dummy.