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http://dx.doi.org/10.5351/KJAS.2006.19.3.481

Estimation and Performance Analysis of Risk Measures using Copula and Extreme Value Theory  

Yeo, Sung-Chil (Department of Applied Statistics, Konkuk University)
Publication Information
The Korean Journal of Applied Statistics / v.19, no.3, 2006 , pp. 481-504 More about this Journal
Abstract
VaR, a tail-related risk measure is now widely used as a tool for a measurement and a management of financial risks. For more accurate measurement of VaR, recently we are particularly concerned about the approach based on extreme value theory rather than the traditional method based on the assumption of normal distribution. However, many studies about the approaches using extreme value theory was done only for the univariate case. In this paper, we discuss portfolio risk measurements with modelling multivariate extreme value distributions by combining copulas and extreme value theory. We also discuss the estimation of ES together with VaR as portfolio risk measures. Finally, we investigate the relative superiority of EVT-copula approach than variance-covariance method through the back-testing of an empirical data.
Keywords
Risk Measure; Value at Risk; Expected Shortfall; Extreme Value Theory; Copulas; Back-testing;
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Times Cited By KSCI : 1  (Citation Analysis)
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