中文摘要：

本文在对资产组合的风险分析研究中以VaR作为风险度量工具,采用基于Pair Copula高维建模方法的混合C藤Copula风险分析模型,构建了反映多个资产收益实际分布和相依性的联合分布函数。该模型对C藤图形化建模工具作了进一步改进,根据变量间相关性强弱确定变量顺序,并对各Pair Copula都依据一定的标准选择最优函数族。以此建立的模型不仅考虑到了维数影响,而且能捕捉到资产组合因子间的相关性差异,从而能更好描述资产组合的相依结构。在此基础上,利用MonteCarlo方法计算了中国外汇市场上七种外汇资产投资组合的VaR,并通过实证分析验证了该模型的有效性。

英文摘要：

A mixed C-vines copula model based on Pair Copula Constructions method was used to construct the practical distribu- tion of multiple asset returns and joint distribution function of dependency for studying risk of portfolio by VaR. The model improves on a graphical modeling tool, namely C vine and allows the variables to be ordered according to their influence and chooses the best families of copula functions for every Pair Copula by a rule. It not only takes into account of the impact of dimensions, but also can capture the difference of the correlation among portfolio factors, so it can describe the dependence structure of the multiple asset returns better. Based on the mixed C-vines copula models, we apply the Monte Carlo methodology to study VaR of a portfolio of seven foreign curren- cies in China, and the validity of the model is proved by empirical analysis.