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Alternative modelling and inference methods for claim size distributions

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  • Raschke, Mathias

Abstract

The upper tail of a claim size distribution of a property line of business is frequently modelled by Pareto distribution. However, the upper tail does not need to be Pareto distributed, extraordinary shapes are possible. Here, the opportunities for the modelling of loss distributions are extended. The basic idea is the adjustment of a base distribution for their tails. The (generalised) Pareto distribution is used as base distribution for different reasons. The upper tail is in the focus and can be modelled well for special cases by a discrete mixture of the base distribution with a combination of the base distribution with an adapting distribution via the product of their survival functions. A kind of smoothed step is realised in this way in the original line function between logarithmic loss and logarithmic exceedance probability. The lower tail can also be adjusted. The new approaches offer the opportunity for stochastic interpretation and are applied to observed losses. For parameter estimation, a modification of the minimum Anderson Darling distance method is used. A new test is suggested to exclude that the observed upper tail is better modelled by a simple Pareto distribution. Q-Q plots are applied, and secondary results are also discussed.

Suggested Citation

  • Raschke, Mathias, 2020. "Alternative modelling and inference methods for claim size distributions," Annals of Actuarial Science, Cambridge University Press, vol. 14(1), pages 1-19, March.
  • Handle: RePEc:cup:anacsi:v:14:y:2020:i:1:p:1-19_1
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    Cited by:

    1. Bennet Skarczinski & Mathias Raschke & Frank Teuteberg, 2023. "Modelling maximum cyber incident losses of German organisations: an empirical study and modified extreme value distribution approach," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 48(2), pages 463-501, April.

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