A VaR Algorithm for Warrants Portfolio

Abstract

Based on Gamma Vega-Cornish Fish methodology, this paper propose the algorithm for calculating VaR via adjusting the quantile under the given confidence level using the four moments (e.g. mean, variance, skewness and kurtosis) of the warrants portfolio return and estimating the variance of portfolio by EWMA methodology. Meanwhile, the proposed algorithm considers the attenuation of the effect of history return on portfolio return of future days. Empirical study shows that, comparing with Gamma-Cornish Fish method and standard normal method, the VaR calculated by Gamma Vega-Cornish Fish can improve the effectiveness of forecasting the portfolio risk by virture of considering the Gamma risk and the Vega risk of the warrants. The significance test is conducted on the calculation results by employing two-tailed test developed by Kupiec. Test results show that the calculated VaRs of the warrants portfolio all pass the significance test under the significance level of 5%.