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Multivariate heavy-tailed models for Value-at-Risk estimation


  • Carlo Marinelli
  • Stefano d'Addona
  • Svetlozar T. Rachev


For purposes of Value-at-Risk estimation, we consider several multivariate families of heavy-tailed distributions, which can be seen as multidimensional versions of Paretian stable and Student's t distributions allowing different marginals to have different tail thickness. After a discussion of relevant estimation and simulation issues, we conduct a backtesting study on a set of portfolios containing derivative instruments, using historical US stock price data.

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  • Carlo Marinelli & Stefano d'Addona & Svetlozar T. Rachev, 2010. "Multivariate heavy-tailed models for Value-at-Risk estimation," Papers 1005.2862,, revised Dec 2011.
  • Handle: RePEc:arx:papers:1005.2862

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    References listed on IDEAS

    1. Platen, Eckhard, 2006. "Portfolio selection and asset pricing under a benchmark approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 370(1), pages 23-29.
    2. Gollier, Christian, 2008. "Understanding saving and portfolio choices with predictable changes in assets returns," Journal of Mathematical Economics, Elsevier, vol. 44(5-6), pages 445-458, April.
    3. Okui, Ryo, 2009. "The optimal choice of moments in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 151(1), pages 1-16, July.
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