A tradeoff between forecast accuracy and the length of an estimation period always exists in forecasting. Longer estimation periods are argued to be less efficient, however, using the forecast encompassing and accuracy test, this study discusses the importance of considering the overall...

This article employs a bivariate poisson jump model to investigate the relationship between the volatility of crude oil and gasoline especially during the period of the Gulf War. We find that greater jumps occurring in crude oil returns will appear in gasoline returns at the same time, but the...

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...

This study adopts the autoregressive conditional jump intensity (ARJI) model proposed by Chan and Maheu [J. Business Econ. Stat. 20 (2002) 377–389] to investigate the impact of news on SIMEX-Nikkei 225 and CME-Nikkei 225 (regards it as the twins). Empirical results demonstrate that the twins...

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...