Effective methods for hedging downside risk during a global financial crisis: Evidence from asian stock index futures

This study investigates futures contracts for five Asian stock indices, namely the Nikkei 225, Kospi 200, MSCI Hong Kong, MSCI Taiwan, and MSCI Singapore indices, using the GARCH, FIGARCH, HYGARCH, and GJR-GARCH models with normal and skewed Student-t innovation distributions. Empirical results indicate that volatility of Asian stock index futures is characterized by long memory. Additionally, owing to the significant parameter estimation of the fat-tail term and the better results obtained via VaR computations based on the Kupiec LR tests, this investigation also confirms that variations in Asian stock index futures exhibit fat tails. Third, empirical results indicate that the HYGARCH model displays superior explanation ability to the other models during insample periods. Fourth, on average, the skewed Student-t GJR-GARCH model outperforms other models during the global financial crisis period. The long memory models thus are not the best models for fitting extreme stock volatility, such as occurred during the global financial crisis period. In contrast, asymmetric models are more suited to fitting the violent stock volatility during the global financial crisis period.