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Improving Modeling of Extreme Events using Generalized Extreme Value Distribution or Generalized Pareto Distribution with Mixing Unconditional Disturbances

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Listed:
  • Suarez, Ronny

Abstract

In this paper an alternative non-parametric historical simulation approach, the Mixing Unconditional Disturbances model with constant volatility, where price paths are generated by reshuffling disturbances for S&P 500 Index returns over the period 1950 - 1998, is used to estimate a Generalized Extreme Value Distribution and a Generalized Pareto Distribution. An ordinary back-testing for period 1999 - 2008 was made to verify this technique, providing higher accuracy returns level under upper bound of the confidence interval for the Block Maxima and the Peak-Over Threshold approaches with Mixing Unconditional Disturbances. This method can be an effective tool to create value for stress-testing valuation.

Suggested Citation

  • Suarez, Ronny, 2009. "Improving Modeling of Extreme Events using Generalized Extreme Value Distribution or Generalized Pareto Distribution with Mixing Unconditional Disturbances," MPRA Paper 17482, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:17482
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    References listed on IDEAS

    as
    1. Younes Bensalah, 2000. "Steps in Applying Extreme Value Theory to Finance: A Review," Staff Working Papers 00-20, Bank of Canada.
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    5. Tompkins, Robert G. & D'Ecclesia, Rita L., 2006. "Unconditional return disturbances: A non-parametric simulation approach," Journal of Banking & Finance, Elsevier, vol. 30(1), pages 287-314, January.
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    More about this item

    Keywords

    Extreme Values; Block Maxima; Peak-Over Threshold; Mixing Unconditional Disturbances;
    All these keywords.

    JEL classification:

    • C0 - Mathematical and Quantitative Methods - - General
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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