Fitting insurance claims to skewed distributions: Are the skew-normal and skew-student good models?

Martin Eling

Insurance: Mathematics and Economics, 2012, vol. 51, issue 2, 239-248

Abstract: This paper analyzes whether the skew-normal and skew-student distributions recently discussed in the finance literature are reasonable models for describing claims in property-liability insurance. We consider two well-known datasets from actuarial science and fit a number of parametric distributions to these data. Also the non-parametric transformation kernel approach is considered as a benchmark model. We find that the skew-normal and skew-student are reasonably competitive compared to other models in the literature when describing insurance data. In addition to goodness-of-fit tests, tail risk measures such as value at risk and tail value at risk are estimated for the datasets under consideration.

Keywords: Goodness of fit; Risk measurement; Skew-normal; Skew-student (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (49)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:insuma:v:51:y:2012:i:2:p:239-248

DOI: 10.1016/j.insmatheco.2012.04.001

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