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Fair Actuarial Values For Deductible Insurance Policies In The Presence Of Parameter Uncertainty

Author

Listed:
  • ARIE HAREL

    (The Zicklin School of Business, Baruch College, The City University of New York, Box B11-220, One Bernard Baruch Way, New York, NY 10010-5585, USA)

  • GIORA HARPAZ

    (The Zicklin School of Business, Baruch College, The City University of New York, Box B10-225, One Bernard Baruch Way, New York, NY 10010-5585, USA)

Abstract

This paper derives the multi-period fair actuarial values for six deductible insurance policies offered in today's insurance markets. The loss in any given period is generated by the Weibull distribution with a known shape parameter but an unknown scale parameter. The insurer is assumed to be a Bayesian decision maker, in the sense that he/she learns sequentially about the unknown scale parameter by observing the realizations of the filed claims. It is shown that the insurer's underlying predictive loss distributions belong to the Burr family, and the multi-period actuarially fair policy value can be derived. With a proper loading, an insurance premium can be quoted. Our major contribution is the analytical derivations of the fair actuarial values for deductible insurance policies in the presence of parameter uncertainty and Bayesian learning.

Suggested Citation

  • Arie Harel & Giora Harpaz, 2007. "Fair Actuarial Values For Deductible Insurance Policies In The Presence Of Parameter Uncertainty," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 10(02), pages 389-397.
    • Handle: RePEc:wsi:ijtafx:v:10:y:2007:i:02:n:s0219024907004159
    DOI: 10.1142/S0219024907004159
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    Cited by:

    1. Fan-chin Kung & Haiyong Liu, 2019. "Underinsurance Caused by Uninsurable Losses in the Public Goods and Personal Assets," Review of Economics & Finance, Better Advances Press, Canada, vol. 15, pages 14-22, February.

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