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Forecasting VaR and Expected Shortfall using Dynamical Systems: A Risk Management Strategy

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  • Cyril Caillault

    (Fortis Investments - Fortis investments)

  • Dominique Guegan

    ()
    (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Paris I - Panthéon-Sorbonne, EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics - Ecole d'Économie de Paris)

Abstract

Using non-parametric and parametric models, we show that the bivariate distribution of an Asian portfolio is not stable along all the period under study. We suggest several dynamic models to compute two market risk measures, the Value at Risk and the Expected Shortfall: the RiskMetrics methodology, the Multivariate GARCH models, the Multivariate Markov-Switching models, the empirical histogram and the dynamic copulas. We discuss the choice of the best method with respect to the policy management of bank supervisors. The copula approach seems to be a good compromise between all these models. It permits taking financial crises into account and obtaining a low capital requirement during the most important crises.

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Bibliographic Info

Paper provided by HAL in its series Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) with number halshs-00375765.

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Date of creation: Apr 2009
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Publication status: Published, Frontiers in finance and economics, 2009, 6, 1, 26-50
Handle: RePEc:hal:cesptp:halshs-00375765

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Keywords: Value at Risk ; Expected Shortfall ; Copulas ; Risk management ; GARCH models ; Markov switching models;

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References

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  1. Cyril Caillault & Dominique Guegan, 2005. "Empirical Estimation of Tail Dependence Using Copulas. Application to Asian Markets," Post-Print halshs-00180865, HAL.
  2. Dominique Guégan & Jing Zhang, 2007. "Pricing bivariate option under GARCH-GH model with dynamic copula : application for Chinese market," Documents de travail du Centre d'Economie de la Sorbonne b07057, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
  3. Y. Malevergne & D. Sornette, 2001. "Testing the Gaussian Copula Hypothesis for Financial Assets Dependences," Papers cond-mat/0111310, arXiv.org.
  4. Dominique Guegan, 2004. "How Can We Define the Long Memory Concept? An Econometric Survey," Econometric Society 2004 Australasian Meetings 361, Econometric Society.
  5. Dominique Guegan, 2007. "La persistance dans les marchés financiers," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00179269, HAL.
  6. Manfred Gilli & Evis Këllezi & Hilda Hysi, . "A Data-Driven Optimization Heuristic for Downside Risk Minimization," Swiss Finance Institute Research Paper Series 06-02, Swiss Finance Institute.
  7. Francq, C. & Zakoian, J. -M., 2001. "Stationarity of multivariate Markov-switching ARMA models," Journal of Econometrics, Elsevier, vol. 102(2), pages 339-364, June.
  8. Granger, Clive W.J. & Terasvirta, Timo & Patton, Andrew J., 2006. "Common factors in conditional distributions for bivariate time series," Journal of Econometrics, Elsevier, vol. 132(1), pages 43-57, May.
  9. Cyril Caillault, Dominique Guégan, 2009. "Forecasting VaR and Expected Shortfall Using Dynamical Systems: A Risk Management Strategy," Frontiers in Finance and Economics, SKEMA Business School, vol. 6(1), pages 26-50, April.
  10. Thomas Mikosch & Catalin Starica, 2004. "Non-stationarities in financial time series, the long range dependence and the IGARCH effects," Econometrics 0412005, EconWPA.
  11. Hamilton, James D., 1988. "Rational-expectations econometric analysis of changes in regime : An investigation of the term structure of interest rates," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 385-423.
  12. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
  13. Eric Jondeau & Michael Rockinger, 2002. "Conditional Dependency of Financial Series: The Copula-GARCH Model," FAME Research Paper Series rp69, International Center for Financial Asset Management and Engineering.
  14. Fermanian, Jean-David, 2005. "Goodness-of-fit tests for copulas," Journal of Multivariate Analysis, Elsevier, vol. 95(1), pages 119-152, July.
  15. Guégan D., 2004. "How Can We Define The Concept of Long Memory? An Econometric Survey," School of Economics and Finance Discussion Papers and Working Papers Series 178, School of Economics and Finance, Queensland University of Technology.
  16. Rockafellar, R. Tyrrell & Uryasev, Stanislav, 2002. "Conditional value-at-risk for general loss distributions," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1443-1471, July.
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Citations

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Cited by:
  1. repec:hal:journl:halshs-00639489 is not listed on IDEAS
  2. Dominique Guégan & Jing Zhang, 2006. "Change analysis of dynamic copula for measuring dependence in multivariate financial data," Cahiers de la Maison des Sciences Economiques b06090, Université Panthéon-Sorbonne (Paris 1).
  3. Dominique Guegan & Wayne Tarrant, 2012. "Viewing Risk Measures as information," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00721350, HAL.
  4. Cyril Caillault & Dominique Guegan, 2009. "Forecasting VaR and Expected Shortfall using Dynamical Systems: A Risk Management Strategy," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00375765, HAL.
  5. Dominique Guegan & Wayne Tarrant, 2012. "On the Necessity of Five Risk Measures," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00721339, HAL.
  6. Dominique Gu/'egan & Wayne Tarrant, 2011. "Viewing Risk Measures as Information," Papers 1111.4417, arXiv.org.
  7. Dominique Gu\'egan & Wayne Tarrant, 2011. "On the Necessity of Five Risk Measures," Papers 1111.4414, arXiv.org.
  8. Dominique Guégan, 2009. "A Meta-Distribution for Non-Stationary Samples," CREATES Research Papers 2009-24, School of Economics and Management, University of Aarhus.

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