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Published in:
2010 | OriginalPaper | Chapter
Estimating Portfolio Risk Using GARCH-EVT-Copula Model: An Empirical Study on Exchange Rate Market
Authors : Zongrun Wang, Yanbo Jin, Yanju Zhou
Published in: Advances in Neural Network Research and Applications
Publisher: Springer Berlin Heidelberg
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This paper introduces GARCH-EVT-Copula model and applies it to study the portfolio risk of exchange rates. Multivariate Copulas including Gaussian Copula, t Copula and Clayton Copula were used to describe the structure and extend the analysis from bivariate to any n-dimension. We apply this methodology to study the returns of a portfolio of four major foreign currencies in China. Our results suggest that the optimal investment allocations are similar across different Copula and confidence levels and the optimal investment concentrates in the USD investment. Generally speaking, t Copula and Clayton Copula can better portray the correlation structure of multiple assets than Normal Copula.