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

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Author Info

  • 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)

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

    Note: View the original document on HAL open archive server: http://halshs.archives-ouvertes.fr/halshs-00375765
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    Related research

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

    This paper has been announced in the following NEP Reports:

    References

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    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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    1. Y. Malevergne & D. Sornette, 2003. "Testing the Gaussian copula hypothesis for financial assets dependences," Quantitative Finance, Taylor and Francis Journals, vol. 3(4), pages 231-250.
    2. Christian Francq & Jean-Michel Zakoïan, 2000. "Stationarity of Multivariate Markov-Switching ARMA Models," Working Papers 2000-32, Centre de Recherche en Economie et Statistique.
    3. Cyril Caillault & Dominique Guegan, 2005. "Empirical estimation of tail dependence using copulas: application to Asian markets," Quantitative Finance, Taylor and Francis Journals, vol. 5(5), pages 489-501.
    4. 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.
    5. Cyril Caillault & Dominique Guegan, 2005. "Empirical Estimation of Tail Dependence Using Copulas. Application to Asian Markets," Post-Print halshs-00180865, HAL.
    6. Thomas Mikosch & Catalin Starica, 2004. "Non-stationarities in financial time series, the long range dependence and the IGARCH effects," Econometrics 0412005, EconWPA.
    7. Dominique Guegan & Jing Zang, 2009. "Pricing bivariate option under GARCH-GH model with dynamic copula: application for Chinese market," European Journal of Finance, Taylor and Francis Journals, vol. 15(7-8), pages 777-795.
    8. Dominique Guegan, 2005. "How can we define the concept of long memory ? An econometric survey," Post-Print halshs-00179343, HAL.
    9. 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.
    10. Dominique Guegan, 2004. "How Can We Define the Long Memory Concept? An Econometric Survey," Econometric Society 2004 Australasian Meetings 361, Econometric Society.
    11. 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.
    12. Fermanian, Jean-David, 2005. "Goodness-of-fit tests for copulas," Journal of Multivariate Analysis, Elsevier, vol. 95(1), pages 119-152, July.
    13. Timo Terasvirta & Clive W.J Granger & Andrew Patton, 2003. "Common factors in conditional distributions for Bivariate time series," FMG Discussion Papers dp455, Financial Markets Group.
    14. Dominique Guegan & Jing Zhang, 2009. "Pricing bivariate option under GARCH-GH model with dynamic copula: application for Chinese market," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00368336, HAL.
    15. 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.
    16. Dominique Guegan, 2007. "La persistance dans les marchés financiers," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00179269, HAL.
    17. 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.
    18. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    19. Dominique Guegan, 2005. "How can we Define the Concept of Long Memory? An Econometric Survey," Econometric Reviews, Taylor and Francis Journals, vol. 24(2), pages 113-149.
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    Citations

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    Cited by:
    1. Dominique Guegan & Jing Zhang, 2010. "Change analysis of a dynamic copula for measuring dependence in multivariate financial data," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00368334, HAL.
    2. 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.
    3. Dominique Gu\'egan & Wayne Tarrant, 2011. "On the Necessity of Five Risk Measures," Papers 1111.4414, arXiv.org.
    4. Dominique Gu/'egan & Wayne Tarrant, 2011. "Viewing Risk Measures as Information," Papers 1111.4417, arXiv.org.
    5. 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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