Evaluation of Hedge Fund Returns Value at Risk Using GARCH Models

The aim of this research paper is to evaluate hedge fund returns Value-at-Risk by using GARCH models. To perform the empirical analysis, one uses the HFRX daily performance hedge fund strategy subindexes and spans the period March 2003 – March 2008. I found that skewness and kurtosis are substantial in the hedge fund returns distribution and the clustering phenomenon is pointed out. These features suggest the use of GARCH models to model the volatility of hedge fund return indexes. Hedge fund return conditional variances are estimated by using linear models (GARCH) and non-linear asymmetric models (EGARCH and TGARCH). Performance of several Value at Risk models is compared; the Gaussian VaR, the student VaR, the cornish fisher VaR, the normal GARCH-type VaR, the student GARCH-type VaR and the cornish fisher GARCH-type VaR. Our results demonstrate that the normal VaR underestimates accurate hedge fund risks while the student and the cornish fisher GARCH-type VaR are more reliable to estimate the potential maximum loss of hedge funds.