一种多资产组合风险度量解决之道：正则藤Copula

为准确地度量包含有多项金融资产的组合的风险，本文提出使用一种新的高维Copula构建方法，正则藤Copula（Canonical Vine Copula），来对多资产间的非线性相关结构进行建模，该函数呈现为一个以一系列成对Copula函数作为节点的“藤”的层叠结构。本文基于上海、香港和台湾三个股票市场对构建该高维Copula函数时各个节点上成对Copula函数类型的选取进行了讨论，并证实了正则藤Copula函数相比传统的多元Copula函数能够更灵活地描述各市场间尾部相关性的复杂形式。样本外风险预测绩效分析和模拟研究均表明，使用正则藤Copula函数确实能够更为稳健和准确地预测组合VaR。

A New Approach for Measuring the Risk of Portfolios with Multiple Assets

In order to accurately measure the risk of portfolios with multiple assets, this paper introduces Canonical Vine Copula, which is constructed hierarchically using a cascade of pair-copulas, to model multivariate non-linear dependence structure. Based on Shanghai, Hong Kong and Taiwan stock markets, this paper discusses the proper way to choose pair- copula functions in the hierarchical construction, and verifies statistically that Canonical Vine Copula could describes the complex patterns of cross-asset dependence in tails more flexibly than traditional multivariate copula functions. Furthermore, the out-of-sample performance of risk forecasts and simulation analysis indicate that, we could obtain more robust and accurate VaR forecasts by using Canonical Vine Copula.