In this study, the generalized autoregressive conditional heteroskedasticity (GARCH) model involving skewed generalized error distribution (SGED) was used to estimate the corresponding volatility and value-at-risk (VaR) measures for various commodities distributed across four types of commodity...

This paper employs three Value-at-Risk (VaR) models (GARJI, ARJI and asymmetric GARCH) to compare the performance of 1-day-ahead VaR estimates. The influences of price jumps and asymmetric information on the performance of VaR are investigated. Two stock indices (Dow Jones and S&P 500) and one...

In this paper we derive a new mean-risk hedge ratio based on the concept of Value at Risk (VaR). The proposed zero-VaR hedge ratio has an analytical solution and it converges to the MV hedge ratio under a pure martingale process or normality. A bivariate constant correlation GARCH(1,1) model...