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A VaR Algorithm for Warrants Portfolio

  • Jun Dai
  • Liyun Ni
  • Xiangrong Wang
  • Weizhong Chen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6124)

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%.

Keywords

Warrant VaR Gamma Risk Vega Risk Gamma Vega-Cornish Fish Gamma-Cornish Fish 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Jun Dai
    • 1
  • Liyun Ni
    • 1
  • Xiangrong Wang
    • 2
  • Weizhong Chen
    • 1
  1. 1.School of Economics and ManagementTongji UniversityShanghaiChina
  2. 2.College of Info Sci & EngiShandong University of Science & TechnologyQingdaoChina

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