沪深股市相关结构分析研究

Research on Dependence Structure Between Shanghai and Shenzhen Stock Markets

在金融市场风险分析中,对金融资产相关结构的讨论有着重要意义,从而引出对如何选取好的相关结构模型来捕捉金融资产间的相关变化规律的讨论。针对这一问题,我们用混合相关结构函数Copula对上海、深圳股票市场进行了相关分析研究,用极值分布刻画了每支股票的边缘分布,用两步估计法对Copula中的参数进行了估计。分析结果表明:混合Copula相关结构能够捕捉金融市场间相关性变化规律,比单个Copula相关结构更灵活,更能全面地反映市场间非对称变化的相关程度和模式,此方法还可以推广到对多种金融资产收益率进行相关性分析。

It is of particular relevance in financial markets if we are required to study the dependence between the financial data. In this situation it is essential to find a good dependent model for reflecting the dependence variety. To this aim, we pay attention to the model M-Copula-GPD. The extreme value and a two-step method are used to study between Shanghai and Shenzhen stock markets. The empirical results show that the model M-Copula-GPD is more flexible than simple Copula functions, and can thoroughly capture the dependence between financial markets. An extended works of modelling the dependence structure of a few financial assets is provided in this paper.