Worst-case reinsurance strategy with likelihood ratio uncertainty

Abstract In this paper, we explore a non-cooperative optimal reinsurance problem incorporating likelihood ratio uncertainty, aiming to minimize the worst-case risk of the total retained loss for the insurer. We establish a general relation between the optimal reinsurance strategy under the reference probability measure and the strategy in the worst-case scenario. This relation can further be generalized to insurance design problems quantified by tail risk measures. We also characterize distortion risk measures for which the insurer’s optimal strategy remains the same in the worst-case scenario. As an application, we determine the optimal policies for the worst-case scenario using an expectile risk measure. Additionally, we propose and explore a cooperative problem, which can be viewed as a general risk sharing problem between two agents in a comonotonic market. We determine the risk measure value and the optimal reinsurance strategy in the worst-case scenario for the insurer and compare the results from the non-cooperative and cooperative models.

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Publication Details

Journal
Astin Bulletin
Published
2025-02-20
DOI
https://doi.org/10.1017/asb.2025.1
Citations
2
Primary Topic
Risk and Portfolio Optimization
Type
article
Field-Weighted Citation Impact
4.21
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article

Worst-case reinsurance strategy with likelihood ratio uncertainty

Fangda Liu, David Landriault, Ziyue Shi
2 citations
Astin Bulletin
Risk and Portfolio Optimization
4.21
article

Worst-case reinsurance strategy with likelihood ratio uncertainty

Fangda Liu, David Landriault, Ziyue Shi
article en
2 citations

Abstract

Abstract In this paper, we explore a non-cooperative optimal reinsurance problem incorporating likelihood ratio uncertainty, aiming to minimize the worst-case risk of the total retained loss for the insurer. We establish a general relation between the optimal reinsurance strategy under the reference probability measure and the strategy in the worst-case scenario. This relation can further be generalized to insurance design problems quantified by tail risk measures. We also characterize distortion risk measures for which the insurer’s optimal strategy remains the same in the worst-case scenario. As an application, we determine the optimal policies for the worst-case scenario using an expectile risk measure. Additionally, we propose and explore a cooperative problem, which can be viewed as a general risk sharing problem between two agents in a comonotonic market. We determine the risk measure value and the optimal reinsurance strategy in the worst-case scenario for the insurer and compare the results from the non-cooperative and cooperative models.

Astin BulletinVol. 55(3)
University of Waterloo (CA)
Openalex Percentile: Top 8%
Risk and Portfolio Optimization
4.21
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