基于尾部依赖的保险业系统性风险度量

从系统性风险的界定出发,综合考虑系统性风险的两个视角,基于保险公司的股票数据探讨保险业的系统性风险.通过构造Kendall协同系数检验整体依赖性和尾部依赖性,以(非对称)尾部依赖性为切入点,构造SV-t模型和厚尾的SV-GED模型,利用AIC准则和Hit检验法对不同依赖结构的copula模型进行筛选.通过实证分析,检测出中国人寿、中国平安和太平洋保险公司的非对称尾部依赖结构,认为保险业可能成为系统性风险传导链条上的一环,并且完全可能自身隐含和集聚系统性风险.结论部分分析了系统性风险的原因,针对如何降低下尾风险依赖提出政策建议,为我国保险业宏观审慎监管提供一些支持材料.

Systemic risk measure in insurance industry based on tail dependence

The concept of systemic risk was defined in this paper to test the systemic risk in China insurance market based on stocks data from the two different angles of view. Take tail dependence, by constructing Kendall coordinate coefficient test, as cut-in spot, SV-t models and fat-tail SV-GED models were constructed to fit the data. Based on AIC information rules and Hit test, the appropriate copula models with different dependence structures were chose. From empirical analysis, unbalance tail dependence structure between China Life, Pingan and CPIC is positive, China insurance market would transfer systemic risk as part of a chain and itself may assemble systemic risk. The reason why there exists systemic risk in insurance market, as well as the suggestions on how to reduce the lower tail dependence, was put out. It may contribute to our Macro-prudential Supervision.