Estimating the Tails of Loss Severity Distributions Using Extreme Value Theory
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In this paper, the authors describe parametric curvefitting methods for modeling extreme fire insurance losses, which revolve around the genelahzed Pareto distribution and are supported by extreme value theory.Abstract:
Good estimates for the tails of loss severity dustrlbutlons are essential for pricing or positioning high-excess loss layers m reinsurance We describe parametric curvefitting inethods for modelling extreme h~storlcal losses These methods revolve around the genelahzed Pareto distribution and are supported by extreme value theory. We summarize relevant theoretical results and provide an extenswe example of thmr application to Danish data on large fire insurance lossesread more
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References
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Book
Modelling Extremal Events: for Insurance and Finance
TL;DR: In this article, an approach to Extremes via Point Processes is presented, and statistical methods for Extremal Events are presented. But the approach is limited to time series analysis for heavy-tailed processes.
Journal ArticleDOI
Statistical Inference Using Extreme Order Statistics
TL;DR: In this article, a method for making statistical inferences about the upper tail of a distribution function is presented for estimating the probabilities of future extremely large observations, where the underlying distribution function satisfies a condition which holds for all common continuous distribution functions.
Journal ArticleDOI
Limiting forms of the frequency distribution of the largest or smallest member of a sample
R. A. Fisher,L. H. C. Tippett +1 more
TL;DR: In this article, the problem of finding the appropriate limiting distribution in any case may be found from the manner in which the probability of exceeding any value x tends to zero as x is increased.