Abstract

A survey of the risk management literature shows that few studies have attempted to take into account financial crisis in market risk measurement, in particular when using a Value-at Risk (VaR) analysis. In this paper, we use models to investigate the effects of subprime crisis on the Value-at-Risk estimation. In this framework, we investigate GARCH family models such as, GARCH, IGARCH, and GJR-GARCH. Each is adjusted based on three residuals distributions; normal, Student and Skewed Student-t. Using American stock market data, we show that dynamic volatility is different between the stability and during crisis periods. The estimation results indicate that the amount of VaR is different during these two time periods. This finding could be explained by the volatility clustering effect. The empirical results show also that GJR-GARCH model performs better in both sub-sample periods, in comparison with GARCH and IGARCH models. Moreover, we conclude that Student-t and Skewed Student-t distributions are preferred in the stable period while the normal distribution is recommended during the turbulent period.  

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