二元极值理论在沪深股市尾部风险度量中的应用

Applications of Bivariate Extreme Value Theory for Measuring Tail Risk between Shanghai and Shenzhen Stock Markets

用二元极值理论对沪深股市联合分布的尾部特征进行了研究。把一种新的极值Copula函数—t-EV-copula应用于二元极值理论。t-EV-copula与Gumble copula的比较分析表明:t-EV-copula不仅能很好地模拟极值数据,而且能够准确的捕捉到上尾、下尾变化;由二元极值理论得到基于t-EV-copula的沪深股市联合分布尾部的二元分布函数并作分布函数图。最后,用VaR作为风险度量进一步描述了联合分布的尾部特征。

The bivariate extreme value theory is applied to research the heavy-tail characteristic of the joint distribution for the Shanghai and Shenzhen stock markets. A new extreme copula——t-EV-copula, compared with the Gumble copula, not only simulate the extreme data very well, but also can catch the upper dependence and the lower dependence, then obtain the function of the tail joint distribution based on the t- EV-copula and it＇s figure is also obtained. At last is used VaR as the risk measure to describe the tail character of the joint distribution.