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...

The choice of an appropriate distribution for return innovations is important in VaR applications owing to its ability to directly affect the estimation quality of the required quantiles. This study investigates the influence of fat-tailed innovation process on the performance of one-day-ahead...

This study extends the one period zero-VaR (Value-at-Risk) hedge ratio proposed by Hung et al. (2005) to the multi-period case and incorporates the hedging horizon into the objective function under VaR framework. The multi-period zero-VaR hedge ratio has several advantages. First, compared to...

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...