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Extreme Value Theory for Tail-Related Risk Measures

  • Evis Këllezi

    (Department of Econometrics and FAME, University of Geneva,switzerland)

  • Manfred Gilli

    (Department of Econometrics, University of Geneva, Switzerland)

Many fields of modern science and engineering have to deal with events which are rare but have significant consequences. Extreme value theory is considered to provide the basis for the statistical modeling of such extremes. The potential of extreme value theory applied to financial problems has only been recognized recently. This paper aims at introducing the fundamentals of extreme value theory as well as practical aspects for estimating and assessing statistical models for tail-related risk measures.

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Paper provided by International Center for Financial Asset Management and Engineering in its series FAME Research Paper Series with number rp18.

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Date of creation: Oct 2000
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Handle: RePEc:fam:rpseri:rp18
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  1. McNeil, Alexander J. & Frey, Rudiger, 2000. "Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 271-300, November.
  2. Longin, Francois M, 1996. "The Asymptotic Distribution of Extreme Stock Market Returns," The Journal of Business, University of Chicago Press, vol. 69(3), pages 383-408, July.
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