Measuring market risk: a copula and extreme value approach
This paper presents a methodology for measuring the risk of a portfolio composed of assets with heteroscedastic return series. In order to obtain good estimates for Value-at-Risk and Expected Shortfall, the model tries to capture as realistically as possible the data generating process for each return series and also the dependence structure that exists at the portfolio level. For this purpose, the individual return series are modelled using GARCH methods with semi-parametric innovations and the dependence structure is defined with the help of a Student t copula. The model built with these techniques is then used for the simulation of a portfolio return distribution that allows the estimation of the risk measures. This methodology is applied to a portfolio of five Romanian stocks and the accuracy of the risk measures is then tested using a backtesting procedure.
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