Nonlinear VaR Model of Options Portfolio Under Multivariate Mixture of Normals Distributions

摘要：

The paper proposes a kind of nonlinear VaR model of options portfolio under heavy-tailed market risk factors. The paper depicts heavy-tailed market risk factors using multivariate mixture of normals distribution,and derives the moment generating function that reflects the change in options portfolio value. Moreover,to make use of the relationship between characteristic function and moment generating function,the paper develops Fourier-Inversion method and adaptive Simpson rule with iterative algorithm of numerical integration into nonlinear VaR model of options portfolio,and calculates the VaR values of portfolio. Numerical results show that the VaR values using Fourier-Inversion method is slight difference from the VaR values using Monte Carlo simulation method. However,the calculation speed using Fourier Inversion method is obviously quicker than the speed using Monte Carlo simulation method.

关键词： option portfolio nonlinear VaR multivariate mixture of normals distributions Fourier-Inversion method

作者: Rongda Chen Dan Cao Qingyang Yu

作者单位: School of Finance,Zhejiang University of Finance and Economics,Hangzhou,310018,China

会议类型: 国际会议

会议名称: The Third International Conference on Business Intelligence and Financial Engineering(第三届商务智能与金融工程国际会议 BIFE 2010)

会议地点: 香港

会议语种:英文

页码: 364-368

在线出版日期: 2010-08-17（万方平台首次上网日期，不代表论文的发表时间）