基于小波极值理论的中国股市风险研究

运用条件风险价值(CVaR)模型实现对市场风险的监控,把小波变换和极值理论结合在一起对CVaR进行估计.第一阶段,用小波方法确定广义Pareto分布的阈值;第二阶段,把基于小波变换的阈值运用到极值理论中,然后运用极值理论估计CVaR.选用香港恒生指数和深证综指进行实证分析,把基于小波变换的极值理论估计的CVaR与条件极值理论估计的CVaR进行比较,根据失败数量和尾部损失检验,发现基于小波变换的极值理论能够提高预测的精准性.

Risk Analysis of Chinese Stock Market Based on Wavelet-Based Extreme Value Theory

Using CVaR (conditional value-at-risk) control market risks. Wavelets and EVT(extreme value theory) were combined to estimate conditional value-at-risk. In the first stage, wavelets were used as a threshold in generalized Pareto distribution, and in the second stage, EVT is applied with a wavelet-based threshold,then we are to eastimate CVaR with extreme thoery .This new model was applied to two major stock markets: the Hang Seng index and the Shenzhen composite index. The relative performance of wavelet-based EVT was benchmarked against the conditional extreme value thoery. The empirical results shows that the wavelet-based extreme value theory increases predictive performance of financial forecasting according to number of violations and tail-loss tests.