基于小波极值理论的中国股市风险研究
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国家自然科学基金资助项目(71071098);上海市一流学科建设资助项目(XTKX2012)


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

    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.

    Abstract:

    The model of conditional value-at-risk (CVaR) was utilized to control market risks.Wavelets technique and extreme value theory (EVT) were combined to estimate the conditional value-at-risk.Wavelets were used as a threshold in generalized Pareto distribution,and EVT was applied with a wavelet-based threshold,then the CVaR was estimated by virtue of the extreme theory.This new model has been applied to two major stock markets:the Hang Seng index and the Shenzhen composite index.The relative performance of the wavelet-based EVT was benchmarked against the conditional extreme value theory.The empirical results show that the wavelet-based EVT improves the predictive performance of financial forecasting according to the number of violations and for the results of tail-loss tests.

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董晓玉,李星野.基于小波极值理论的中国股市风险研究[J].上海理工大学学报,2015,37(2):187-193.

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  • 收稿日期:2013-11-11
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  • 在线发布日期: 2015-05-19
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