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Value at Risk Computation in a Non-Stationary Setting

Author

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  • Dominique Guegan

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

Abstract

This chapter recalls the main tools useful to compute Value at Risk associated with a m-dimensional portfolio. Then, the limitations of the use of these tools is explained, as soon as non-stationarities are observed in time series. Indeed, specific behaviours observed by financial assets, like volatility, jumps, explosions, and pseudo-seasonalities, provoke non-stationarities which affect the distribution function of the portfolio. Thus, a new way for computing VaR is proposed which allows the potential non-invariance of the m-dimensional portfolio distribution function to be avoided.

Suggested Citation

  • Dominique Guegan, 2010. "Value at Risk Computation in a Non-Stationary Setting," PSE-Ecole d'économie de Paris (Postprint) halshs-00511995, HAL.
    • Handle: RePEc:hal:pseptp:halshs-00511995
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00511995
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    References listed on IDEAS

    as
    1. Dominique Guegan & Pierre-André Maugis, 2008. "New prospects on vines," Documents de travail du Centre d'Economie de la Sorbonne b08095, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Mar 2010.
    2. Cyril Caillault & Dominique Guegan, 2005. "Empirical estimation of tail dependence using copulas: application to Asian markets," Quantitative Finance, Taylor & Francis Journals, vol. 5(5), pages 489-501.
    3. Cătălin Stărică & Clive Granger, 2005. "Nonstationarities in Stock Returns," The Review of Economics and Statistics, MIT Press, vol. 87(3), pages 503-522, August.
    4. Cyril Caillault & Dominique Guegan, 2009. "Forecasting VaR and Expected Shortfall using Dynamical Systems: A Risk Management Strategy," PSE-Ecole d'économie de Paris (Postprint) halshs-00375765, HAL.
    5. Aas, Kjersti & Czado, Claudia & Frigessi, Arnoldo & Bakken, Henrik, 2009. "Pair-copula constructions of multiple dependence," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 182-198, April.
    6. Cyril Caillault & Dominique Guegan, 2009. "Forecasting VaR and Expected Shortfall using Dynamical Systems: A Risk Management Strategy," Post-Print halshs-00375765, HAL.
    Full references (including those not matched with items on IDEAS)

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