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Var For Quadratic Portfolio'S With Generalized Laplace Distributed Returns

Author

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  • Raymond BRUMMELHUIS
  • Jules Sadefo-Kamdem

Abstract

This paper is concerned with the e±cient analytical computation of Value-at-Risk (VaR) for portfolios of assets depending quadratically on a large number of joint risk factors that follows a multivariate Generalized Laplace Distribution. Our approach is designed to supplement the usual Monte-Carlo techniques, by providing an asymptotic formula for the quadratic portfolio's cumulative distribution function, together with explicit error-estimates. The application of these methods is demonstrated using some financial applications examples.

Suggested Citation

  • Raymond BRUMMELHUIS & Jules Sadefo-Kamdem, 2009. "Var For Quadratic Portfolio'S With Generalized Laplace Distributed Returns," Working Papers 09-06, LAMETA, Universitiy of Montpellier, revised Jun 2009.
  • Handle: RePEc:lam:wpaper:09-06
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    File URL: http://www.lameta.univ-montp1.fr/Documents/DR2009-06.pdf
    File Function: First version, 2009
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    References listed on IDEAS

    as
    1. Paul Glasserman & Philip Heidelberger & Perwez Shahabuddin, 2002. "Portfolio Value-at-Risk with Heavy-Tailed Risk Factors," Mathematical Finance, Wiley Blackwell, vol. 12(3), pages 239-269.
    2. Sadefo Kamdem, J. & Genz, A., 2008. "Approximation of multiple integrals over hyperboloids with application to a quadratic portfolio with options," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3389-3407, March.
    3. Jules SADEFO KAMDEM, 2004. "Value-at-Risk and Expected Shortfall for Quadratic Portfolio of Securities with Mixture of Elliptic Distribution Risk Factors," Computing in Economics and Finance 2004 12, Society for Computational Economics.
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    Cited by:

    1. Sadefo Kamdem, J. & Genz, A., 2008. "Approximation of multiple integrals over hyperboloids with application to a quadratic portfolio with options," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3389-3407, March.

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