金融市场的相关性分析--Copula-GARCH模型及其应用

作为一种全新的分析方法，Copula技术不仅可以有效地捕捉金融时间序列间的相关性，还可用于研究整个金融市场的特性、投资组合的选择及风险分析等其他金融问题。结合t-GARCH模型和Copula函数，建立Copula-GARCH模型并对上海股市各板块指数收益率序列间的条件相关性进行分析。结果表明，不同板块的指数收益率序列具有不同的边缘分布，各序列间有很强的正相关关系，条件相关具有时变性，各序列间相关性的变化趋势极为相似。

Dependence Analysis of Finance Markets:Copula-GARCH Model and Its Application

As a new methodology that measures dependence, Copula technique can be also used widely in studying the characteristics of financial markets, portfolio aggregation and risk analysis etc. Conditional dependence of index returns series in Shanghai stock market is analyzed using the Copula-GARCH model combined the t-GARCH model with a Copula function. The empirical results show that different index returns series have different marginal distribution. There are strong positive correlations between these series. We found that the conditional dependence between these series is time- varying, and that the variety trend is very likeness.