IDEAS home Printed from https://ideas.repec.org/p/hal/wpaper/hal-00496300.html
   My bibliography  Save this paper

Mean-Variance efficient strategies in proportional reinsurance under group correlation in a Gaussian framework

Author

Listed:
  • Flavio Pressacco

    (Università degli Studi di Udine - University of Udine [Italie])

  • Paolo Serafini

    (DIMI - Dipartimento di Matematica e Informatica - Universita Udine - Università degli Studi di Udine - University of Udine [Italie])

  • Laura Ziani

    (Università degli Studi di Udine - University of Udine [Italie])

Abstract

The paper concerns optimal mean-variance proportional reinsurance under group correlation. In order to solve the corresponding constrained quadratic optimization problem, we make large recourse both to the smart friendly technique originally proposed by B. de Finetti in his pioneering paper and to the well known Karush-Kuhn-Tucker conditions for constrained optimization. We offer closed form results and insightful considerations about the problem. In detail, we give closed form formulas to express the efficient mean-variance retention set both in the retention space and in the mean-variance one.

Suggested Citation

  • Flavio Pressacco & Paolo Serafini & Laura Ziani, 2010. "Mean-Variance efficient strategies in proportional reinsurance under group correlation in a Gaussian framework," Working Papers hal-00496300, HAL.
  • Handle: RePEc:hal:wpaper:hal-00496300
    Note: View the original document on HAL open archive server: https://hal.science/hal-00496300
    as

    Download full text from publisher

    File URL: https://hal.science/hal-00496300/document
    Download Restriction: no
    ---><---

    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:hal:wpaper:hal-00496300. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.