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Budget-constrained optimal reinsurance design under coherent risk measures

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  • Ka Chun Cheung
  • Wing Fung Chong
  • Ambrose Lo

Abstract

Reinsurance is a versatile risk management strategy commonly employed by insurers to optimize their risk profile. In this paper, we study an optimal reinsurance design problem minimizing a general law-invariant coherent risk measure of the net risk exposure of a generic insurer, in conjunction with a general law-invariant comonotonic additive convex reinsurance premium principle and a premium budget constraint. Due to its intrinsic generality, this contract design problem encompasses a wide body of optimal reinsurance models commonly encountered in practice. A three-step solution scheme is presented. Firstly, the objective and constraint functions are exhibited in the so-called Kusuoka's integral representations. Secondly, the mini-max theorem for infinite dimensional spaces is applied to interchange the infimum on the space of indemnities and the supremum on the space of probability measures. Thirdly, the recently developed Neyman–Pearson methodology due to Lo (2017a) is adopted to solve the resulting infimum problem. Analytic and transparent expressions for the optimal reinsurance policy are provided, followed by illustrative examples.

Suggested Citation

  • Ka Chun Cheung & Wing Fung Chong & Ambrose Lo, 2019. "Budget-constrained optimal reinsurance design under coherent risk measures," Scandinavian Actuarial Journal, Taylor & Francis Journals, vol. 2019(9), pages 729-751, October.
    • Handle: RePEc:taf:sactxx:v:2019:y:2019:i:9:p:729-751
    DOI: 10.1080/03461238.2019.1598891
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    Cited by:

    1. Corina Birghila & Tim J. Boonen & Mario Ghossoub, 2023. "Optimal insurance under maxmin expected utility," Finance and Stochastics, Springer, vol. 27(2), pages 467-501, April.

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