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ORDERING PROPERTIES OF EXTREME CLAIM AMOUNTS FROM HETEROGENEOUS PORTFOLIOS

Published online by Cambridge University Press:  29 April 2019

Yiying Zhang
Affiliation:
School of Statistics and Data Science, LPMC and KLMDASRNankai UniversityTianjin 300071, P.R. China E-Mail: zhangyiying@outlook.com
Xiong Cai
Affiliation:
College of Applied SciencesBeijing University of TechnologyBeijing 100124, P.R. China E-Mail: xcai@emails.bjut.edu.cn
Peng Zhao*
Affiliation:
School of Mathematics and StatisticsJiangsu Normal UniversityXuzhou 221116, P.R. China E-Mail: zhaop@jsnu.edu.cn

Abstract

In the context of insurance, the smallest and largest claim amounts turn out to be crucial to insurance analysis since they provide useful information for determining annual premium. In this paper, we establish sufficient conditions for comparing extreme claim amounts arising from two sets of heterogeneous insurance portfolios according to various stochastic orders. It is firstly shown that the weak supermajorization order between the transformed vectors of occurrence probabilities implies the usual stochastic ordering between the largest claim amounts when the claim severities are weakly stochastic arrangement increasing. Secondly, sufficient conditions are established for the right-spread ordering and the convex transform ordering of the smallest claim amounts arising from heterogeneous dependent insurance portfolios with possibly different number of claims. In the setting of independent multiple-outlier claims, we study the effects of heterogeneity among sample sizes on the stochastic properties of the largest and smallest claim amounts in the sense of the hazard rate ordering and the likelihood ratio ordering. Numerical examples are provided to highlight these theoretical results as well. Not only can our results be applied in the area of actuarial science, but also they can be used in other research fields including reliability engineering and auction theory.

Information

Type
Research Article
Copyright
Copyright © Astin Bulletin 2019 

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