Log-supermodularity of weight functions, ordering weighted losses, and the loading monotonicity of weighted premiums

Hristo S. Sendov, Ying Wang and Ricardas Zitikis

Insurance: Mathematics and Economics, 2011, vol. 48, issue 2, 257-264

Abstract: The paper is motivated by a problem concerning the monotonicity of insurance premiums with respect to their loading parameter: the larger the parameter, the larger the insurance premium is expected to be. This property, usually called the loading monotonicity, is satisfied by premiums that appear in the literature. The increased interest in constructing new insurance premiums has raised a question as to what weight functions would produce loading-monotonic premiums. In this paper, we demonstrate a decisive role of log-supermodularity or, equivalently, of total positivity of order 2 (TP2) in answering this question. As a consequence, we establish-at a stroke-the loading monotonicity of a number of well-known insurance premiums, and offer a host of further weight functions, and consequently of premiums, thus illustrating the power of the herein suggested methodology for constructing loading-monotonic insurance premiums.

Keywords: Insurance; premium; Weighted; premium; Weighted; distribution; Log-supermodularity; Supermodularity; Submodularity; Likelihood; ratio; order; Total; positivity; of; order; 2; Esscher; premium; Conditional; tail; expectation; Kamps; premium; Wang; premium; Distortion; premium; Decision; under; uncertainty (search for similar items in EconPapers)
Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:insuma:v:48:y:2011:i:2:p:257-264

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