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http://dx.doi.org/10.5351/KJAS.2017.30.3.363

New composite distributions for insurance claim sizes  

Jung, Daehyeon (Department of Statistics, Yeungnam University)
Lee, Jiyeon (Department of Statistics, Yeungnam University)
Publication Information
The Korean Journal of Applied Statistics / v.30, no.3, 2017 , pp. 363-376 More about this Journal
Abstract
The insurance market is saturated and its growth engine is exhausted; consequently, the insurance industry is now in a low growth period with insurance companies that face a fierce competitive environment. In such a situation, it will be an important issue to find the probability distributions that can explain the flow of insurance claims, which are the basis of the actuarial calculation of the insurance product. Insurance claims are generally known to be well fitted by lognormal distributions or Pareto distributions biased to the left with a thick tail. In recent years, skew normal distributions or skew t distributions have been considered reasonable distributions for describing insurance claims. Cooray and Ananda (2005) proposed a composite lognormal-Pareto distribution that has the advantages of both lognormal and Pareto distributions and they also showed the composite distribution has a higher fitness than single distributions. In this paper, we introduce new composite distributions based on skew normal distributions or skew t distributions and apply them to Danish fire insurance claim data and US indemnity loss data to compare their performance with the other composite distributions and single distributions.
Keywords
composite distribution; skew normal distribution; skew t distribution; Danish fire insurance claim data; US indemnity loss data; maximum likelihood estimator; AIC;
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