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The folded EGB2 distribution and its application to financial return data

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  • Fischer, Matthias J.

Abstract

In the literature there are several generalzations of the standard logistic distribution. Most of them are included in the generalized logistic distribution of type 4 or EGB2 distribution. However, this four parameter family fails in modeling skewness absolutly greater than 2 and kurtosis higher than 9. To remove the shortcoming, and additional parameter is introduced. Unfortunately, there is now no closed form for the probability density function of the generalized EGB2, briefely called FEGB2 of generalized logistic distribution of type 5. However it can be approximated numerically, for example by saddlepoint approximation or numerical integration methods. Finally, FEGB2 is used for modeling returns of financial data.

Suggested Citation

  • Fischer, Matthias J., 2000. "The folded EGB2 distribution and its application to financial return data," Discussion Papers 32/2000, Friedrich-Alexander University Erlangen-Nuremberg, Chair of Statistics and Econometrics.
    • Handle: RePEc:zbw:faucse:322000
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    6. Stefan Mittnik & Marc Paolella & Svetlozar Rachev, 1998. "Unconditional and Conditional Distributional Models for the Nikkei Index," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 5(2), pages 99-128, May.
    7. Zelterman, D., 1987. "Parameter estimation in the generalized logistic distribution," Computational Statistics & Data Analysis, Elsevier, vol. 5(3), pages 177-184.
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    Cited by:

    1. Svetlozar Rachev & Frank J. Fabozzi & Boryana Racheva-Iotova & Abootaleb Shirvani, 2017. "Option Pricing with Greed and Fear Factor: The Rational Finance Approach," Papers 1709.08134, arXiv.org, revised Mar 2020.
    2. Fischer, Matthias J., 2000. "The Esscher-EGB2 option pricing model," Discussion Papers 31/2000, Friedrich-Alexander University Erlangen-Nuremberg, Chair of Statistics and Econometrics.

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