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Extreme value statistics and wind storm losses: A case study

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  • Holger Rootzén
  • Nader Tajvidi

Abstract

Statistical extreme value theory provides a flexible and theoretically well motivated approach to the study of large losses in insurance. We give a brief review of the modem version of this theory and a “step by step” example of how to use it in large claims insurance. The discussion is based on a detailed investigation of a wind storm insurance problem. New results include a simulation study of estimators in the peaks over thresholds method with Generalised Pareto excesses, a discussion of Pareto and lognormal modelling and of methods to detect trends. Further results concern the use of meteorological information in the wind storm insurance and, of course, the results of the study of the wind storm claims.

Suggested Citation

  • Holger Rootzén & Nader Tajvidi, 1997. "Extreme value statistics and wind storm losses: A case study," Scandinavian Actuarial Journal, Taylor & Francis Journals, vol. 1997(1), pages 70-94.
    • Handle: RePEc:taf:sactxx:v:1997:y:1997:i:1:p:70-94
    DOI: 10.1080/03461238.1997.10413979
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    Cited by:

    1. Stupfler, Gilles & Yang, Fan, 2018. "Analyzing And Predicting Cat Bond Premiums: A Financial Loss Premium Principle And Extreme Value Modeling," ASTIN Bulletin, Cambridge University Press, vol. 48(1), pages 375-411, January.

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