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Measuring market risk: a copula and extreme value approach

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  • Alexandru Stanga

Abstract

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.

Suggested Citation

  • Alexandru Stanga, 2008. "Measuring market risk: a copula and extreme value approach," Advances in Economic and Financial Research - DOFIN Working Paper Series 13, Bucharest University of Economics, Center for Advanced Research in Finance and Banking - CARFIB.
  • Handle: RePEc:cab:wpaefr:13
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    File URL: http://www.dofin.ase.ro/Working%20papers/Stanga%20Alexandru/alexandru.stanga.dissertation.pdf
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    References listed on IDEAS

    as
    1. Cotter, John & Dowd, Kevin, 2006. "Extreme spectral risk measures: An application to futures clearinghouse margin requirements," Journal of Banking & Finance, Elsevier, vol. 30(12), pages 3469-3485, December.
    2. Rosenberg, Joshua V. & Schuermann, Til, 2006. "A general approach to integrated risk management with skewed, fat-tailed risks," Journal of Financial Economics, Elsevier, vol. 79(3), pages 569-614, March.
    3. Tae-Hwy Lee & Yong Bao & Burak Saltoglu, 2006. "Evaluating predictive performance of value-at-risk models in emerging markets: a reality check," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(2), pages 101-128.
    4. Bouye, Eric & Durlleman, Valdo & Nikeghbali, Ashkan & Riboulet, Gaƫl & Roncalli, Thierry, 2000. "Copulas for finance," MPRA Paper 37359, University Library of Munich, Germany.
    5. L. K. Hotta & E. C. Lucas & H. P Palaro, 2008. "Estimation of VaR Using Copula and Extreme Value Theory," Multinational Finance Journal, Multinational Finance Journal, vol. 12(3-4), pages 205-218, September.
    6. Longin, Francois M., 2000. "From value at risk to stress testing: The extreme value approach," Journal of Banking & Finance, Elsevier, vol. 24(7), pages 1097-1130, July.
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    More about this item

    Keywords

    Value-at-Risk;

    Statistics

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