IDEAS home Printed from https://ideas.repec.org/a/taf/sactxx/v2020y2020i4p342-375.html
   My bibliography  Save this article

Optimal excess-of-loss reinsurance contract with ambiguity aversion in the principal-agent model

Author

Listed:
  • Ailing Gu
  • Frederi G. Viens
  • Yang Shen

Abstract

We discuss an optimal excess-of-loss reinsurance contract in a continuous-time principal-agent framework where the surplus of the insurer (agent/he) is described by a classical Cramér-Lundberg (C-L) model. In addition to reinsurance, the insurer and the reinsurer (principal/she) are both allowed to invest their surpluses into a financial market containing one risk-free asset (e.g. a short-rate account) and one risky asset (e.g. a market index). In this paper, the insurer and the reinsurer are ambiguity averse and have specific modeling risk aversion preferences for the insurance claims (this relates to the jump term in the stochastic models) and the financial market's risk (this encompasses the models' diffusion term). The reinsurer designs a reinsurance contract that maximizes the exponential utility of her terminal wealth under a worst-case scenario which depends on the retention level of the insurer. By employing the dynamic programming approach, we derive the optimal robust reinsurance contract, and the value functions for the reinsurer and the insurer under this contract. In order to provide a more explicit reinsurance contract and to facilitate our quantitative analysis, we discuss the case when the claims follow an exponential distribution; it is then possible to show explicitly the impact of ambiguity aversion on the optimal reinsurance.

Suggested Citation

  • Ailing Gu & Frederi G. Viens & Yang Shen, 2020. "Optimal excess-of-loss reinsurance contract with ambiguity aversion in the principal-agent model," Scandinavian Actuarial Journal, Taylor & Francis Journals, vol. 2020(4), pages 342-375, April.
  • Handle: RePEc:taf:sactxx:v:2020:y:2020:i:4:p:342-375
    DOI: 10.1080/03461238.2019.1669218
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/03461238.2019.1669218
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/03461238.2019.1669218?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Emma Kroell & Sebastian Jaimungal & Silvana M. Pesenti, 2023. "Optimal Robust Reinsurance with Multiple Insurers," Papers 2308.11828, arXiv.org, revised Mar 2024.
    2. Cao, Jingyi & Li, Dongchen & Young, Virginia R. & Zou, Bin, 2023. "Reinsurance games with two reinsurers: Tree versus chain," European Journal of Operational Research, Elsevier, vol. 310(2), pages 928-941.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:sactxx:v:2020:y:2020:i:4:p:342-375. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/sact .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.