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Incorporating model uncertainty into optimal insurance contract design

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  • Ch. Pflug, Georg
  • Timonina-Farkas, Anna
  • Hochrainer-Stigler, Stefan

Abstract

In stochastic optimization models, the optimal solution heavily depends on the selected probability model for the scenarios. However, the scenario models are typically chosen on the basis of statistical estimates and are therefore subject to model error. We demonstrate here how the model uncertainty can be incorporated into the decision making process. We use a nonparametric approach for quantifying the model uncertainty and a minimax setup to find model-robust solutions. The method is illustrated by a risk management problem involving the optimal design of an insurance contract.

Suggested Citation

  • Ch. Pflug, Georg & Timonina-Farkas, Anna & Hochrainer-Stigler, Stefan, 2017. "Incorporating model uncertainty into optimal insurance contract design," Insurance: Mathematics and Economics, Elsevier, vol. 73(C), pages 68-74.
    • Handle: RePEc:eee:insuma:v:73:y:2017:i:c:p:68-74
    DOI: 10.1016/j.insmatheco.2016.11.008
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    References listed on IDEAS

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    1. Pflug, Georg Ch. & Pichler, Alois & Wozabal, David, 2012. "The 1/N investment strategy is optimal under high model ambiguity," Journal of Banking & Finance, Elsevier, vol. 36(2), pages 410-417.
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    7. Georg Pflug & David Wozabal, 2007. "Ambiguity in portfolio selection," Quantitative Finance, Taylor & Francis Journals, vol. 7(4), pages 435-442.
    8. Raviv, Artur, 1979. "The Design of an Optimal Insurance Policy," American Economic Review, American Economic Association, vol. 69(1), pages 84-96, March.
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    Citations

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    Cited by:

    1. Corina Birghila & Tim J. Boonen & Mario Ghossoub, 2020. "Optimal Insurance under Maxmin Expected Utility," Papers 2010.07383, arXiv.org.
    2. Liu, Haiyan & Mao, Tiantian, 2022. "Distributionally robust reinsurance with Value-at-Risk and Conditional Value-at-Risk," Insurance: Mathematics and Economics, Elsevier, vol. 107(C), pages 393-417.
    3. Birghila, Corina & Pflug, Georg Ch., 2019. "Optimal XL-insurance under Wasserstein-type ambiguity," Insurance: Mathematics and Economics, Elsevier, vol. 88(C), pages 30-43.
    4. Stefan Hochrainer-Stigler & Juraj Balkovič & Kadri Silm & Anna Timonina-Farkas, 2019. "Large scale extreme risk assessment using copulas: an application to drought events under climate change for Austria," Computational Management Science, Springer, vol. 16(4), pages 651-669, October.
    5. Corina Birghila & Tim J. Boonen & Mario Ghossoub, 2023. "Optimal insurance under maxmin expected utility," Finance and Stochastics, Springer, vol. 27(2), pages 467-501, April.
    6. Jun Cai & Zhanyi Jiao & Tiantian Mao, 2024. "Worst-case values of target semi-variances with applications to robust portfolio selection," Papers 2410.01732, arXiv.org, revised Oct 2024.
    7. Boonen, Tim J. & Jiang, Wenjun, 2024. "Robust insurance design with distortion risk measures," European Journal of Operational Research, Elsevier, vol. 316(2), pages 694-706.

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