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 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...

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...

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...