FAIR ACTUARIAL VALUES FOR DEDUCTIBLE INSURANCE POLICIES IN THE PRESENCE OF PARAMETER UNCERTAINTY

Arie Harel () and Giora Harpaz ()
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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

International Journal of Theoretical and Applied Finance (IJTAF), 2007, vol. 10, issue 02, 389-397

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.

Keywords: Weibull loss distribution; Bayesian learning; Burr predictive loss distribution; fair actuarial values; deductible insurance policies (search for similar items in EconPapers)
Date: 2007
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Citations: View citations in EconPapers (1)

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DOI: 10.1142/S0219024907004159

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