Estimating risk of foreign exchange portfolio: Using VaR and CVaR based on GARCH–EVT-Copula model
Estimating risk of foreign exchange portfolio: Using VaR and CVaR based on GARCH–EVT-Copula model
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DOI：
10.1016/j.physa.2010.07.012
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发表时间：
2010-11
影响因子：
3.3
通讯作者：
Zongrun Wang;Xiao-hong Chen;Yanbo Jin;Yan-ju Zhou
中科院分区：
文献类型：
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作者：
Zongrun Wang;Xiao-hong Chen;Yanbo Jin;Yan-ju Zhou
本文介绍了GARCH-EVT-Copula模型，并将其应用于外汇投资组合的风险研究。利用Gaussian Copula、t Copula和克莱顿Copula等多变量Copula函数描述投资组合的风险结构，并将分析从二元问题扩展到n维资产配置问题。本文应用该方法研究了美元、欧元、日元和港币四种主要外币的组合收益。我们的研究结果表明，最优投资配置是相似的不同Copula和信心水平。此外，我们发现最优投资集中在美元投资。总的来说，t Copula和克莱顿Copula比Normal Copula更好地刻画了多个资产的相关性结构。
This paper introduces GARCH–EVT-Copula model and applies it to study the risk of foreign exchange portfolio. Multivariate Copulas, including Gaussian, t and Clayton ones, were used to describe a portfolio risk structure, and to extend the analysis from a bivariate to an n-dimensional asset allocation problem. We apply this methodology to study the returns of a portfolio of four major foreign currencies in China, including USD, EUR, JPY and HKD. Our results suggest that the optimal investment allocations are similar across different Copulas and confidence levels. In addition, we find that the optimal investment concentrates on the USD investment. Generally speaking, t Copula and Clayton Copula better portray the correlation structure of multiple assets than Normal Copula.