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EVIM: A Software Package for Extreme Value Analysis in MATLAB

Author

Listed:
  • Gençay Ramazan

    (University of Windsor)

  • Selçuk Faruk

    (Bilkent University)

  • Ulugülyagci Abdurrahman

    (Bilkent University)

Abstract

From the practitioners' point of view, one of the most interesting questions that tail studies can answer is what are the extreme movements that can be expected in financial markets? Have we already seen the largest ones or are we going to experience even larger movements? Are there theoretical processes that can model the type of fat tails that come out of our empirical analysis? Answers to such questions are essential for sound risk management of financial exposures. It turns out that we can answer these questions within the framework of the extreme value theory. This paper provides a step-by-step guideline for extreme value analysis in the MATLAB environment with several examples.

Suggested Citation

  • Gençay Ramazan & Selçuk Faruk & Ulugülyagci Abdurrahman, 2001. "EVIM: A Software Package for Extreme Value Analysis in MATLAB," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 5(3), pages 1-29, October.
    • Handle: RePEc:bpj:sndecm:v:5:y:2001:i:3:n:al1
    DOI: 10.2202/1558-3708.1080
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    References listed on IDEAS

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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. Jansen, Dennis W & de Vries, Casper G, 1991. "On the Frequency of Large Stock Returns: Putting Booms and Busts into Perspective," The Review of Economics and Statistics, MIT Press, vol. 73(1), pages 18-24, February.
    3. Ghose, Devajyoti & Kroner, Kenneth F., 1995. "The relationship between GARCH and symmetric stable processes: Finding the source of fat tails in financial data," Journal of Empirical Finance, Elsevier, vol. 2(3), pages 225-251, September.
    4. Gençay, Ramazan & Dacorogna, Michel & Muller, Ulrich A. & Pictet, Olivier & Olsen, Richard, 2001. "An Introduction to High-Frequency Finance," Elsevier Monographs, Elsevier, edition 1, number 9780122796715.
    5. McNeil, Alexander J., 1997. "Estimating the Tails of Loss Severity Distributions Using Extreme Value Theory," ASTIN Bulletin, Cambridge University Press, vol. 27(1), pages 117-137, May.
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    Cited by:

    1. Sheri Markose & Amadeo Alentorn, 2005. "Option Pricing and the Implied Tail Index with the Generalized Extreme Value (GEV) Distribution," Computing in Economics and Finance 2005 397, Society for Computational Economics.

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