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Value at Risk Computation in a Non-Stationary Setting

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  • Dominique Guegan

    ()
    (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Paris 1 - Panthéon-Sorbonne, EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics - Ecole d'Économie de Paris)

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    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.

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    File URL: http://halshs.archives-ouvertes.fr/docs/00/51/19/95/PDF/guegan_VaR_book_2010.pdf
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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-00511995.

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    Date of creation: 2010
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    Publication status: Published, Handbook on Model Risk : Measuring, managing and mitigating model risk, lessons from financial crisis, John Wiley (Ed.), 2010, 431-454 - chapter 19
    Handle: RePEc:hal:cesptp:halshs-00511995

    Note: View the original document on HAL open archive server: http://halshs.archives-ouvertes.fr/halshs-00511995
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    Web page: http://hal.archives-ouvertes.fr/

    Related research

    Keywords: Non-stationarity - Value-at-Risk - Dynamic copula -Meta-distribution - POT method.;

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    1. Dominique Guegan & Pierre-André Maugis, 2010. "New Prospects on Vines," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00348884, HAL.
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