Forecasting Hedge Funds Volatility: A Risk Management Approach

Abstract

We evaluate the performance of volatility and Value-at-Risk models for hedge fund indexes over the period from January 1994 to December 2003. The exponentially weighted sample variance (EWMA) and E-GARCH models have the best volatility forecast performance for hedge funds in terms of statistical loss functions. In contrast for traditional assets, the best volatility model is the simple sample variance. There is evidence that hedge fund volatility is less persistent that stocks and bonds volatility. We find that the critical decision in selecting a Value-at-Risk model for hedge funds is the distributional assumption. However, in contrast with traditional assets for which the normal distribution presents the best performance, the t-student and, especially the Cornish-Fisher expansion, distributional assumptions present the best performance.

Keywords: Hedge Funds, Volatility, Value at Risk

JEL Classification: C5, G10