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Polynomial Series Expansions and Moment Approximations for Conditional Mean Risk Sharing of Insurance Losses

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  • Michel Denuit

    (UCLouvain)

  • Christian Y. Robert

    (Laboratory in Finance, Insurance - LFA CREST - Center for Research in Economics and Statistics, ENSAE)

Abstract

This paper exploits the representation of the conditional mean risk sharing allocations in terms of size-biased transforms to derive effective approximations within insurance pools of limited size. Precisely, the probability density functions involved in this representation are expanded with respect to the Gamma density and its associated Laguerre orthonormal polynomials, or with respect to the Normal density and its associated Hermite polynomials when the size of the pool gets larger. Depending on the thickness of the tails of the loss distributions, the latter may be replaced with their Esscher transform (or exponential tilting) of negative order. The numerical method then consists in truncating the series expansions to a limited number of terms. This results in an approximation in terms of the first moments of the individual loss distributions. Compound Panjer-Katz sums are considered as an application. The proposed method is compared with the well-established Panjer recursive algorithm. It appears to provide the analyst with reliable approximations that can be used to tune system parameters, before performing exact calculations.

Suggested Citation

  • Michel Denuit & Christian Y. Robert, 2022. "Polynomial Series Expansions and Moment Approximations for Conditional Mean Risk Sharing of Insurance Losses," Methodology and Computing in Applied Probability, Springer, vol. 24(2), pages 693-711, June.
    • Handle: RePEc:spr:metcap:v:24:y:2022:i:2:d:10.1007_s11009-021-09881-7
    DOI: 10.1007/s11009-021-09881-7
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    References listed on IDEAS

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    1. Denuit, Michel & Dhaene, Jan, 2012. "Convex order and comonotonic conditional mean risk sharing," Insurance: Mathematics and Economics, Elsevier, vol. 51(2), pages 265-270.
    2. Joakim Munkhammar & Lars Mattsson & Jesper Rydén, 2017. "Polynomial probability distribution estimation using the method of moments," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-14, April.
    3. Rob Kaas & Marc Goovaerts & Jan Dhaene & Michel Denuit, 2008. "Modern Actuarial Risk Theory," Springer Books, Springer, edition 2, number 978-3-540-70998-5, September.
    4. Denuit, Michel, 2019. "Size-Biased Transform And Conditional Mean Risk Sharing, With Application To P2p Insurance And Tontines," ASTIN Bulletin, Cambridge University Press, vol. 49(3), pages 591-617, September.
    5. Sundt, Bjorn, 2003. "Some recursions for moments of compound distributions," Insurance: Mathematics and Economics, Elsevier, vol. 33(3), pages 487-496, December.
    6. Denuit, Michel, 2019. "Size-biased transform and conditional mean risk sharing, with application to P2P insurance and tontines," LIDAM Discussion Papers ISBA 2019010, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    7. Denuit, Michel, 2019. "Size-biased transform and conditional mean risk sharing, with application to P2P insurance and tontines," LIDAM Reprints ISBA 2019038, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
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    Cited by:

    1. Denuit, Michel & Robert, Christian Y., 2023. "From risk reduction to risk elimination by conditional mean risk sharing of independent losses," Insurance: Mathematics and Economics, Elsevier, vol. 108(C), pages 46-59.

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