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Optimal Insurance to Maximize RDEU Under a Distortion-Deviation Premium Principle

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  • Xiaoqing Liang
  • Ruodu Wang
  • Virginia Young

Abstract

In this paper, we study an optimal insurance problem for a risk-averse individual who seeks to maximize the rank-dependent expected utility (RDEU) of her terminal wealth, and insurance is priced via a general distortion-deviation premium principle. We prove necessary and sufficient conditions satisfied by the optimal solution and consider three ambiguity orders to further determine the optimal indemnity. Finally, we analyze examples under three distortion-deviation premium principles to explore the specific conditions under which no insurance or deductible insurance is optimal.

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  • Xiaoqing Liang & Ruodu Wang & Virginia Young, 2021. "Optimal Insurance to Maximize RDEU Under a Distortion-Deviation Premium Principle," Papers 2107.02656, arXiv.org, revised Feb 2022.
  • Handle: RePEc:arx:papers:2107.02656
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    References listed on IDEAS

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    1. Ghossoub, Mario, 2019. "Optimal insurance under rank-dependent expected utility," Insurance: Mathematics and Economics, Elsevier, vol. 87(C), pages 51-66.
    2. R. Rockafellar & Stan Uryasev & Michael Zabarankin, 2006. "Generalized deviations in risk analysis," Finance and Stochastics, Springer, vol. 10(1), pages 51-74, January.
    3. Wang, Shaun S. & Young, Virginia R., 1998. "Ordering risks: Expected utility theory versus Yaari's dual theory of risk," Insurance: Mathematics and Economics, Elsevier, vol. 22(2), pages 145-161, June.
    4. Chi, Yichun & Zhuang, Sheng Chao, 2020. "Optimal insurance with belief heterogeneity and incentive compatibility," Insurance: Mathematics and Economics, Elsevier, vol. 92(C), pages 104-114.
    5. Yichun Chi & Ming Zhou, 2017. "Optimal Reinsurance Design: A Mean-Variance Approach," North American Actuarial Journal, Taylor & Francis Journals, vol. 21(1), pages 1-14, January.
    6. Promislow, S.David & Young, Virginia R., 2005. "Unifying framework for optimal insurance," Insurance: Mathematics and Economics, Elsevier, vol. 36(3), pages 347-364, June.
    7. Wang, Qiuqi & Wang, Ruodu & Wei, Yunran, 2020. "Distortion Riskmetrics On General Spaces," ASTIN Bulletin, Cambridge University Press, vol. 50(3), pages 827-851, September.
    8. Hong, Chew Soo & Karni, Edi & Safra, Zvi, 1987. "Risk aversion in the theory of expected utility with rank dependent probabilities," Journal of Economic Theory, Elsevier, vol. 42(2), pages 370-381, August.
    9. Ruodu Wang & Yunran Wei & Gordon E. Willmot, 2020. "Characterization, Robustness, and Aggregation of Signed Choquet Integrals," Mathematics of Operations Research, INFORMS, vol. 45(3), pages 993-1015, August.
    10. Carole Bernard & Xuedong He & Jia-An Yan & Xun Yu Zhou, 2015. "Optimal Insurance Design Under Rank-Dependent Expected Utility," Mathematical Finance, Wiley Blackwell, vol. 25(1), pages 154-186, January.
    11. Wang, Shaun, 1996. "Premium Calculation by Transforming the Layer Premium Density," ASTIN Bulletin, Cambridge University Press, vol. 26(1), pages 71-92, May.
    12. Young, Virginia R., 1999. "Optimal insurance under Wang's premium principle," Insurance: Mathematics and Economics, Elsevier, vol. 25(2), pages 109-122, November.
    13. Quiggin, John, 1982. "A theory of anticipated utility," Journal of Economic Behavior & Organization, Elsevier, vol. 3(4), pages 323-343, December.
    14. Shaun, Wang, 1995. "Insurance pricing and increased limits ratemaking by proportional hazards transforms," Insurance: Mathematics and Economics, Elsevier, vol. 17(1), pages 43-54, August.
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    Cited by:

    1. Liang, Xiaoqing & Jiang, Wenjun & Zhang, Yiying, 2023. "Optimal insurance design under mean-variance preference with narrow framing," Insurance: Mathematics and Economics, Elsevier, vol. 112(C), pages 59-79.
    2. Boonen, Tim J. & Jiang, Wenjun, 2022. "Bilateral risk sharing in a comonotone market with rank-dependent utilities," Insurance: Mathematics and Economics, Elsevier, vol. 107(C), pages 361-378.
    3. Jingyi Cao & Dongchen Li & Virginia R. Young & Bin Zou, 2024. "Optimal Insurance to Maximize Exponential Utility when Premium is Computed by a Convex Functional," Papers 2401.08094, arXiv.org.
    4. Tim J. Boonen & Xia Han, 2023. "Optimal insurance with mean-deviation measures," Papers 2312.01813, arXiv.org.

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