Fitting Insurance Claims to Skewed Distributions: Are Skew-Normal and Skew-Student Good Models?
Journal
Insurance: Mathematics and Economics
ISSN
0167-6687
ISSN-Digital
1873-5959
Type
journal article
Date Issued
2012-09
Author(s)
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.
Language
English
Keywords
Goodness of fit
Risk measurement
Skew-normal
Skew-student
HSG Classification
contribution to scientific community
Refereed
Yes
Publisher
Elsevier
Publisher place
Amsterdam
Volume
51
Number
2
Start page
239
End page
248
Pages
10
Subject(s)
Division(s)
Eprints ID
211267