In this paper, we use the skewed t copula with a DCC (Dynamic Conditional Correlation) model to capture the time-varying asymmetric tail dependence among MSCI US, Europe and Emerging markets. The empirical results show that it is important to take account of asymmetric tail dependence when measuring extreme tail risk and forming international portfolio. We find the emerging markets can provide a good contribution to diversifying tail risk. Meanwhile, compared with the normal copula and t copula, the skewed t copula can produce superior out-of-sample portfolio performance in minimizing expected shortfall.

中文翻译：

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国际股票市场的时变非对称尾部依赖

在本文中，我们使用带有 DCC（动态条件相关）模型的偏斜t copula 来捕捉 MSCI 美国、欧洲和新兴市场之间随时间变化的非对称尾部依赖性。实证结果表明，在衡量极端尾部风险和形成国际投资组合时，考虑非对称尾部依赖性很重要。我们发现新兴市场可以为分散尾部风险做出很好的贡献。同时，与正常的 copula 和t copula 相比，倾斜的t copula 可以在最小化预期缺口方面产生更好的样本外投资组合性能。