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Optimal Premium allocation understop-loss insurance using exposure curves
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Date
2022-1-01
Author
Mert, Özenç Murat
Kestel, Ayşe Sevtap
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Determining the retention level in the stop-loss insurance risk premium for both insurerand reinsurer is an important factor in pricing. This paper aims to set optimal reinsurancewith respect to the joint behavior of the insurer and the reinsurer under stop-loss contracts.The dependence between the costs of insurer and reinsurer is expressed as a function ofretention (d) and maximum-cap (m) levels. Based on the maximum degree of correlation,the optimal levels for d and m are derived under certain claim distributions (Pareto,Gamma and Inverse Gamma). Accordingly, the risk premium and exposure curves forboth parties are based on the selected distributions. Quantification of the premium shareover derived exposure curves based on the optimized retention and maximum levels andthe maximum loss risk is obtained using VaR and CVaR as risk measures.
Subject Keywords
Stop-loss reinsurance
,
Optimal retention
,
Optimal cap
,
Premium share
,
Exposure curves
,
Risk measures
URI
https://hdl.handle.net/11511/102471
Journal
HACETTEPE JOURNAL OF MATHEMATICS AND STATISTICS
DOI
https://doi.org/10.15672/hujms.xx
Collections
Graduate School of Applied Mathematics, Article
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Determining the retention level in the stop-loss insurance risk premium for both insurer and reinsurer is an important factor in pricing. This paper aims to set optimal reinsurance with respect to the joint behavior of the insurer and the reinsurer under stop-loss contracts. The dependence between the costs of insurer and reinsurer is expressed as a function of retention (d) and maximum-cap (m) levels. Based on the maximum degree of correlation, the optimal levels for d and m are derived under certain claim...
Optimal premium allocation under stop-loss insurance using exposure curves
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Ö. M. Mert and A. S. Kestel, “Optimal Premium allocation understop-loss insurance using exposure curves,”
HACETTEPE JOURNAL OF MATHEMATICS AND STATISTICS
, vol. 1, no. 1, pp. 1–20, 2022, Accessed: 00, 2023. [Online]. Available: https://hdl.handle.net/11511/102471.
