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

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Author Info

  • Cyril Caillault, Dominique Guégan

    ()
    (Fortis Investments, London)

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

Article provided by SKEMA Business School in its journal Frontiers in Finance and Economics.

Volume (Year): 6 (2009)
Issue (Month): 1 (April)
Pages: 26-50

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Handle: RePEc:ffe:journl:v:6:y:2009:i:1:p:26-50

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Related research

Keywords: Value at risk; expected shortfall; copulas; risk management; GARCH models; Markov switching models;

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References

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  1. Fermanian, Jean-David, 2005. "Goodness-of-fit tests for copulas," Journal of Multivariate Analysis, Elsevier, vol. 95(1), pages 119-152, July.
  2. repec:hal:cesptp:halshs-00179269 is not listed on IDEAS
  3. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
  4. 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.
  5. M. Gilli & E. Kellezi & H. Hysi, 2006. "A Data-Driven Optimization Heuristic for Downside Risk Minimization," Computing in Economics and Finance 2006 355, Society for Computational Economics.
  6. 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.
  7. Y. Malevergne & D. Sornette, 2001. "Testing the Gaussian Copula Hypothesis for Financial Assets Dependences," Finance 0111003, EconWPA.
  8. repec:hal:cesptp:halshs-00375765 is not listed on IDEAS
  9. Cyril Caillault & Dominique Guegan, 2005. "Empirical Estimation of Tail Dependence Using Copulas. Application to Asian Markets," Post-Print halshs-00180865, HAL.
  10. Dominique Guegan & Jing Zang, 2009. "Pricing bivariate option under GARCH-GH model with dynamic copula: application for Chinese market," The European Journal of Finance, Taylor & Francis Journals, vol. 15(7-8), pages 777-795.
  11. 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.
  12. Dominique Guegan, 2005. "How can we Define the Concept of Long Memory? An Econometric Survey," Econometric Reviews, Taylor & Francis Journals, vol. 24(2), pages 113-149.
  13. Thomas Mikosch & Catalin Starica, 2004. "Non-stationarities in financial time series, the long range dependence and the IGARCH effects," Econometrics 0412005, EconWPA.
  14. 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.
  15. Christian Francq & Jean-Michel Zakoïan, 2000. "Stationarity of Multivariate Markov-Switching ARMA Models," Working Papers 2000-32, Centre de Recherche en Economie et Statistique.
  16. Dominique Guegan, 2004. "How Can We Define the Long Memory Concept? An Econometric Survey," Econometric Society 2004 Australasian Meetings 361, Econometric Society.
  17. 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. Dominique Guégan, 2009. "A Meta-Distribution for Non-Stationary Samples," CREATES Research Papers 2009-24, School of Economics and Management, University of Aarhus.
  2. repec:hal:cesptp:halshs-00639489 is not listed on IDEAS
  3. Dominique Gu/'egan & Wayne Tarrant, 2011. "Viewing Risk Measures as Information," Papers 1111.4417, arXiv.org.
  4. Dominique Guegan & Wayne Tarrant, 2011. "Viewing risk measures as information," Documents de travail du Centre d'Economie de la Sorbonne 11054, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
  5. Dominique Gu\'egan & Wayne Tarrant, 2011. "On the Necessity of Five Risk Measures," Papers 1111.4414, arXiv.org.
  6. repec:hal:cesptp:halshs-00189141 is not listed on IDEAS
  7. repec:hal:cesptp:halshs-00460901 is not listed on IDEAS
  8. Dominique Guegan & Wayne Tarrant, 2012. "On the Necessity of Five Risk Measures," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00721339, HAL.
  9. D. Guegan & J. Zhang, 2010. "Change analysis of a dynamic copula for measuring dependence in multivariate financial data," Quantitative Finance, Taylor & Francis Journals, vol. 10(4), pages 421-430.
  10. 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.
  11. repec:hal:journl:halshs-00639489 is not listed on IDEAS

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