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Predictive Stop-Loss Premiums

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  • Hürlimann, Werner

Abstract

Based on a representation of the aggregate claims random variable as linear combination of counting random variables, a linear multivariate Bayesian model of risk theory is defined. In case of the classical risk theoretical assumptions, that is conditional Poisson likelihood counting variates and Gamma structural density, the model is shown to identify with a Bayesian version of the collective model of risk theory. An interesting multivariate credibility formula for the predictive mean is derived. A new type of recursive algorithm, called three-stage nested recursive scheme, allows to evaluate the predictive density and associated predictive stop-loss premiums in an effective way.

Suggested Citation

  • Hürlimann, Werner, 1993. "Predictive Stop-Loss Premiums," ASTIN Bulletin, Cambridge University Press, vol. 23(1), pages 55-76, May.
    • Handle: RePEc:cup:astinb:v:23:y:1993:i:01:p:55-76_00
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