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Model selection based on Lorenz and concentration curves, Gini indices and convex order

Michel Denuit, Dominik Sznajder and Julien Trufin

Insurance: Mathematics and Economics, 2019, vol. 89, issue C, 128-139

Abstract: In order to determine an appropriate amount of premium, statistical goodness-of-fit criteria must be supplemented with actuarial ones when assessing performance of a given candidate pure premium. In this paper, concentration curves and Lorenz curves are shown to provide actuaries with effective tools to evaluate whether a premium is appropriate or to compare two competing alternatives. The idea is to compare the premium income for sub-portfolios gathering low risks (identified as low by means of the premiums under consideration) to the true one, or equivalently, to the actual losses. Numerical illustrations performed on hypothetical data and real ones demonstrate the usefulness of the proposed approach.

Keywords: Pricing; Risk classification; Concentration curve; Lorenz curve; GLM; GBM; Trees; Neural networks (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:eee:insuma:v:89:y:2019:i:c:p:128-139

DOI: 10.1016/j.insmatheco.2019.09.001

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Insurance: Mathematics and Economics is currently edited by R. Kaas, Hansjoerg Albrecher, M. J. Goovaerts and E. S. W. Shiu

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