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Optimal reinsurance under risk and uncertainty on Orlicz hearts

Author

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  • Kong, Dezhou
  • Liu, Lishan
  • Wu, Yonghong

Abstract

In the paper, we study two classes of optimal reinsurance problems on Orlicz hearts in which both the insurer and reinsurer face risk and uncertainty. Based on Balbás et al. (2015) and Rockafellar and Royset (2015b), we first establish the robust representations for the mixed CVaR relative to the set of priors PU0. Then we introduce the general reinsurance premium principle and the general optimal reinsurance problems, which include most of the existing problems as special cases. The necessary and sufficient optimality conditions of the optimal reinsurance problems are obtained by different dual approaches under more general assumptions.

Suggested Citation

  • Kong, Dezhou & Liu, Lishan & Wu, Yonghong, 2018. "Optimal reinsurance under risk and uncertainty on Orlicz hearts," Insurance: Mathematics and Economics, Elsevier, vol. 81(C), pages 108-116.
    • Handle: RePEc:eee:insuma:v:81:y:2018:i:c:p:108-116
    DOI: 10.1016/j.insmatheco.2017.10.006
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    References listed on IDEAS

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    1. R. Rockafellar & Stan Uryasev & Michael Zabarankin, 2006. "Generalized deviations in risk analysis," Finance and Stochastics, Springer, vol. 10(1), pages 51-74, January.
    2. Cui, Wei & Yang, Jingping & Wu, Lan, 2013. "Optimal reinsurance minimizing the distortion risk measure under general reinsurance premium principles," Insurance: Mathematics and Economics, Elsevier, vol. 53(1), pages 74-85.
    3. Ken Seng Tan & Chengguo Weng, 2014. "Empirical Approach for Optimal Reinsurance Design," North American Actuarial Journal, Taylor & Francis Journals, vol. 18(2), pages 315-342, April.
    4. Zhuang, Sheng Chao & Weng, Chengguo & Tan, Ken Seng & Assa, Hirbod, 2016. "Marginal Indemnification Function formulation for optimal reinsurance," Insurance: Mathematics and Economics, Elsevier, vol. 67(C), pages 65-76.
    5. Balbás, Alejandro & Balbás, Beatriz & Balbás, Raquel & Heras, Antonio, 2015. "Optimal reinsurance under risk and uncertainty," Insurance: Mathematics and Economics, Elsevier, vol. 60(C), pages 61-74.
    6. Samuel Drapeau & Michael Kupper, 2013. "Risk Preferences and Their Robust Representation," Mathematics of Operations Research, INFORMS, vol. 38(1), pages 28-62, February.
    7. Gilboa, Itzhak & Schmeidler, David, 1989. "Maxmin expected utility with non-unique prior," Journal of Mathematical Economics, Elsevier, vol. 18(2), pages 141-153, April.
    8. Patrick Cheridito & Tianhui Li, 2009. "Risk Measures On Orlicz Hearts," Mathematical Finance, Wiley Blackwell, vol. 19(2), pages 189-214, April.
    9. Balbás, Alejandro & Balbás, Beatriz & Heras, Antonio, 2009. "Optimal reinsurance with general risk measures," Insurance: Mathematics and Economics, Elsevier, vol. 44(3), pages 374-384, June.
    10. Chi, Yichun & Tan, Ken Seng, 2013. "Optimal reinsurance with general premium principles," Insurance: Mathematics and Economics, Elsevier, vol. 52(2), pages 180-189.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Arai, Takuji & Asano, Takao & Nishide, Katsumasa, 2019. "Optimal initial capital induced by the optimized certainty equivalent," Insurance: Mathematics and Economics, Elsevier, vol. 85(C), pages 115-125.

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    More about this item

    Keywords

    Risk and uncertainty; Orlicz heart; Robust representation; Optimal reinsurance problem; Dual approach;
    All these keywords.

    JEL classification:

    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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