基于藤copula-CAViaR方法的股市风险溢出效应研究

为准确揭示金融风险溢出效应,建立藤copula-CAViaR模型来估计多元条件联合分布,进而推导CoVaR类风险测度方法.该方法既能刻画多个金融市场间非线性的关联关系,也能描述金融市场间"多对一"的风险溢出效应,主要包括三个步骤:第一,使用CAViaR模型拟合单个金融市场收益的边缘分布特征;第二,运用藤copula方法刻画多个金融市场收益间的关联结构;第三,基于边缘分布特征与关联结构,得到多元条件联合分布并计算CoVaR类风险测度,实现金融风险溢出效应刻画.选取上证综指、标普500和日经225等股指数据进行实证研究,结果表明:相比于发生利好事件,美国和日本股票市场(独立或同时)发生更为严重危机事件对中国股票市场影响更加明显,呈现出"风险分担、收益不共享"的总体格局.

Investigating risk spillover effects among stock markets: A vine copula-CAViaR approach

In order to accurately investigate financial risk spillover effects, we construct a vine copula-CAViaR model to estimate the joint distribution and then derive a CoVaR risk measure. Our method is able to explore nonlinear relationships among financial markets and measure their risk spillover effects in a "multiple-to-one" pattern. It contains three main steps. First, we apply the CAViaR model to fit the marginal return distribution of a single financial market. Second, we use the vine copula technique to model dependence among multiple financial markets. Third, we derive the joint returns distribution using the fitted marginal returns distribution and estimated dependence structure, and calculate CoVaR-type risk measure. The efficacy of the novel method is illustrated through empirical studies on Shanghai composite index, SP 500 and Nikkei 225 stock indices. The empirical results show that the impacts of more serious crisis events happened in US or (and) Japanese on Chinese stock market are larger than those of positive events, which can be summarized as "risk shared without profit sharing".