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Optimal reinsurance under the α-maxmin mean-variance criterion

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  • Zhang, Liming
  • Li, Bin

Abstract

This paper studies an optimal reinsurance problem under the α-maximin mean-variance criterion proposed in Li et al. (2016). We generalize (Li et al., 2016) by considering a full range of ambiguity preferences and allowing for general form reinsurance contracts. For equilibrium reinsurance strategies, we find that the excess-of-loss form is unique for ambiguity-averse preferences but may not be optimal or unique for ambiguity-loving preferences. An insurer who is more ambiguous to the reference measure retains less risk if she is ambiguity-averse but does not necessarily retain more risk if she is ambiguity-loving and her ambiguity level is high. Our finding suggests that a highly ambiguity-loving preference may only manifest when the ambiguity level is very low, and hence, consistent with empirical studies, demonstrates that decision makers can be ambiguity-loving if they consider themselves more knowledgeable or competent than the other players.

Suggested Citation

  • Zhang, Liming & Li, Bin, 2021. "Optimal reinsurance under the α-maxmin mean-variance criterion," Insurance: Mathematics and Economics, Elsevier, vol. 101(PB), pages 225-239.
  • Handle: RePEc:eee:insuma:v:101:y:2021:i:pb:p:225-239
    DOI: 10.1016/j.insmatheco.2021.08.004
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    References listed on IDEAS

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    Cited by:

    1. Cao, Jingyi & Li, Dongchen & Young, Virginia R. & Zou, Bin, 2022. "Stackelberg differential game for insurance under model ambiguity," Insurance: Mathematics and Economics, Elsevier, vol. 106(C), pages 128-145.
    2. Yuchen Li & Zongxia Liang & Shunzhi Pang, 2022. "Continuous-Time Monotone Mean-Variance Portfolio Selection," Papers 2211.12168, arXiv.org, revised Jan 2024.

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    More about this item

    Keywords

    Alpha-maxmin mean-variance criterion; Optimal reinsurance; Ambiguity-loving preferences; Non-unique equilibrium; Time inconsistency;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C62 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Existence and Stability Conditions of Equilibrium
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies

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