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Extreme Distribution of a Generalized Stochastic Volatility Model

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  • Aliou Diop

    (IDHE - Institutions et Dynamiques Historiques de l'Economie - ENS Cachan - École normale supérieure - Cachan - UP1 - Université Paris 1 Panthéon-Sorbonne - UP8 - Université Paris 8 Vincennes-Saint-Denis - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique)

  • Dominique Guegan

    (IDHE - Institutions et Dynamiques Historiques de l'Economie - ENS Cachan - École normale supérieure - Cachan - UP1 - Université Paris 1 Panthéon-Sorbonne - UP8 - Université Paris 8 Vincennes-Saint-Denis - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique)

Abstract

We study the asymptotic behaviour of the extreme values of a stochastic volatility model when the noise follows a generalized error distribution extreme. We provide a Monte Carlo experiment to illustrate th choice of the assumptions. We deal also with the finite sample behaviour of the normalized maxima.

Suggested Citation

  • Aliou Diop & Dominique Guegan, 2003. "Extreme Distribution of a Generalized Stochastic Volatility Model," Post-Print halshs-00188535, HAL.
    • Handle: RePEc:hal:journl:halshs-00188535
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00188535
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    References listed on IDEAS

    as
    1. Ghysels, E. & Harvey, A. & Renault, E., 1995. "Stochastic Volatility," Papers 95.400, Toulouse - GREMAQ.
    2. Breidt, F. Jay & Crato, Nuno & de Lima, Pedro, 1998. "The detection and estimation of long memory in stochastic volatility," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 325-348.
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