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Optimal insurance in the presence of insurer's loss limit

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  • Zhou, Chunyang
  • Wu, Wenfeng
  • Wu, Chongfeng

Abstract

In this paper we consider the optimal insurance problem when the insurer has a loss limit constraint. Under the assumptions that the insurance price depends only on the policy's actuarial value, and the insured seeks to maximize the expected utility of his terminal wealth, we show that coverage above a deductible up to a cap is the optimal contract, and the relaxation of insurer's loss limit will increase the insured's expected utility. When the insurance price is given by the expected value principle, we show that a positive loading factor is a sufficient and necessary condition for the deductible to be positive. Moreover, with the expected value principle, we show that the optimal deductible derived in our model is not greater (lower) than that derived in Arrow's model if the insured's preference displays increasing (decreasing) absolute risk aversion. Therefore, when the insured has an IARA (DARA) utility function, compared to Arrow model, the insurance policy derived in our model provides more (less) coverage for small losses, and less coverage for large losses. Furthermore, we prove that the optimal insurance derived in our model is an inferior (normal) good for the insured with a DARA (IARA) utility function, consistent with the finding in the previous literature. Being inferior, the insurance can also be a Giffen good. Under the assumption that the insured's initial wealth is greater than a certain level, we show that the insurance is not a Giffen good if the coefficient of the insured's relative risk aversion is lower than 1.

Suggested Citation

  • Zhou, Chunyang & Wu, Wenfeng & Wu, Chongfeng, 2010. "Optimal insurance in the presence of insurer's loss limit," Insurance: Mathematics and Economics, Elsevier, vol. 46(2), pages 300-307, April.
  • Handle: RePEc:eee:insuma:v:46:y:2010:i:2:p:300-307
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    References listed on IDEAS

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    Cited by:

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    3. Yichun Chi & Xun Yu Zhou & Sheng Chao Zhuang, 2020. "Variance Contracts," Papers 2008.07103, arXiv.org.
    4. Chi, Yichun, 2018. "Insurance choice under third degree stochastic dominance," Insurance: Mathematics and Economics, Elsevier, vol. 83(C), pages 198-205.
    5. Ghossoub, Mario, 2019. "Budget-constrained optimal insurance without the nonnegativity constraint on indemnities," Insurance: Mathematics and Economics, Elsevier, vol. 84(C), pages 22-39.
    6. Christopher Gaffney & Adi Ben-Israel, 2016. "A simple insurance model: optimal coverage and deductible," Annals of Operations Research, Springer, vol. 237(1), pages 263-279, February.
    7. Christopher Gaffney & Adi Ben-Israel, 2016. "A simple insurance model: optimal coverage and deductible," Annals of Operations Research, Springer, vol. 237(1), pages 263-279, February.
    8. Lu, ZhiYi & Liu, LePing & Meng, ShengWang, 2013. "Optimal reinsurance with concave ceded loss functions under VaR and CTE risk measures," Insurance: Mathematics and Economics, Elsevier, vol. 52(1), pages 46-51.
    9. Liu, Ying & Li, Xiaozhong & Liu, Yinli, 2015. "The bounds of premium and optimality of stop loss insurance under uncertain random environments," Insurance: Mathematics and Economics, Elsevier, vol. 64(C), pages 273-278.
    10. Wang, Ching-Ping & Huang, Hung-Hsi, 2016. "Optimal insurance contract under VaR and CVaR constraints," The North American Journal of Economics and Finance, Elsevier, vol. 37(C), pages 110-127.
    11. Tan, Ken Seng & Weng, Chengguo & Zhang, Yi, 2011. "Optimality of general reinsurance contracts under CTE risk measure," Insurance: Mathematics and Economics, Elsevier, vol. 49(2), pages 175-187, September.
    12. Zheng, Yanting & Cui, Wei, 2014. "Optimal reinsurance with premium constraint under distortion risk measures," Insurance: Mathematics and Economics, Elsevier, vol. 59(C), pages 109-120.
    13. Mi Chen & Wenyuan Wang & Ruixing Ming, 2016. "Optimal Reinsurance Under General Law-Invariant Convex Risk Measure and TVaR Premium Principle," Risks, MDPI, vol. 4(4), pages 1-12, December.

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