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Two maxentropic approaches to determine the probability density of compound risk losses

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  • Gomes-Gonçalves, Erika
  • Gzyl, Henryk
  • Mayoral, Silvia

Abstract

Here we present an application of two maxentropic procedures to determine the probability density distribution of a compound random variable describing aggregate risk, using only a finite number of empirically determined fractional moments. The two methods that we use are the Standard method of Maximum Entropy (SME) and the method of Maximum Entropy in the Mean (MEM). We analyze the performance and robustness of these two procedures in several numerical examples, in which the frequency of losses is Poisson and the individual losses are lognormal random variables. We shall verify that the reconstructions obtained pass a variety of statistical quality criteria, and provide good estimations of VaR and TVaR, which are important measures for risk management purposes. As side product of the work, we obtain a rather accurate numerical description of the density of such compound random variable.

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  • Gomes-Gonçalves, Erika & Gzyl, Henryk & Mayoral, Silvia, 2015. "Two maxentropic approaches to determine the probability density of compound risk losses," Insurance: Mathematics and Economics, Elsevier, vol. 62(C), pages 42-53.
    • Handle: RePEc:eee:insuma:v:62:y:2015:i:c:p:42-53
    DOI: 10.1016/j.insmatheco.2015.03.001
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    References listed on IDEAS

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    Cited by:

    1. Gomes-Gonçalves, Erika & Gzyl, Henryk & Mayoral, Silvia, 2016. "Loss data analysis: Analysis of the sample dependence in density reconstruction by maxentropic methods," Insurance: Mathematics and Economics, Elsevier, vol. 71(C), pages 145-153.
    2. Kartashova Olga Ivanovna & Molchanova Olga Vladimirovna & Axana Turgaeva, 2018. "Insurance Risks Management Methodology," JRFM, MDPI, vol. 11(4), pages 1-15, October.
    3. Gomes-Gonçalves, Erika & Gzyl, Henryk & Mayoral, Silvia, 2015. "Maxentropic approach to decompound aggregate risk losses," Insurance: Mathematics and Economics, Elsevier, vol. 64(C), pages 326-336.

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