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Performance analysis of EVT-GARCH-Copula models for estimating portfolio Value at Risk
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 Title & Authors
Performance analysis of EVT-GARCH-Copula models for estimating portfolio Value at Risk
Lee, Sang Hun; Yeo, Sung Chil;
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Value at Risk (VaR) is widely used as an important tool for risk management of financial institutions. In this paper we discuss estimation and back testing for VaR of the portfolio composed of KOSPI, Dow Jones, Shanghai, Nikkei indexes. The copula functions are adopted to construct the multivariate distributions of portfolio components from marginal distributions that combine extreme value theory and GARCH models. Volatility models with t distribution of the error terms using Gaussian, t, Clayton and Frank copula functions are shown to be more appropriate than the other models, in particular the model using the Frank copula is shown to be the best.
Value at Risk;extreme value theory;GARCH models;copula;back testing;
 Cited by
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