基于动态因子Copula模型的行业间系统性风险分析

国际金融市场间的相关关系以及系统性风险受到很多学者的重视，本文则以我国股市的行业指数作为研究对象进行实证研究。通过构建动态因子Copula模型，文章对行业的日收益率数据进行了动态相关性分析，并基于风险预期占比度量了我国行业之间系统性风险的溢出效应。本文分析了2006年1月4日至2016年7月1日的28个行业指数数据，基于GAS动态负荷因子的变化路径来刻画其相关关系，通过风险预期占比来研究行业间的风险溢出效应。研究表明，各个行业指数收益率之间存在较强的关联性。就单个行业来说，化工行业与其他行业关系最为不稳定。就金融与非金融行业而言，金融行业对非金融行业的影响较大且较为平稳。本文所得研究结果可以为投资者和风险管理者在进行决策时提供一定的指导。

Analysis of Systemic Risk among Industries via Dynamic Factor Copulas

The correlation among international financial markets and the research on systemic risk have been emphasized by scholars. This paper focuses on the domestic stock sector indexes for empirical analysis. In this article, a dynamic factor Copula model is constructed to analyze the dynamic relationship of the daily returns, and further to measure the spillover effects of systemic risks among industries based on EPR (Expected proportion of industries at risk). For empirical research, this paper chooses intra-day stock prices of respective 28 industries, ranging from January 4^th 2006 to July 1^st 2016. Based on the path of dynamic factor loading or EPR, the correlations and risk spillover effects between industries can be discussed. Studies show that close correlations exist between returns of sector indexes. In terms of a single trade, the stock index of chemical industry is most susceptible to other industries.In terms of financial and non-financial sector, it is suggested that the financial sectors have a great and relatively stable influence on the non-financial ones. These results could provide investors and risk managers with guidance in decisions-making.