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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/87703 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/87703 http://eprints.org/relation/issmallThumbnailVersionOf https://pure.iiasa.ac.at/id/document/87703 104134 1 317107 document 104134 indexcodes.txt text/x-c d2a1e3105efe715fbe3c542f12d92cb8 MD5 11024 2023-12-17 10:25:30 https://pure.iiasa.ac.at/id/eprint/15937/6/indexcodes.txt 15937 6 6 text/x-c other Generate index codes conversion from text to indexcodes en public

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/87703 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/87703 http://eprints.org/relation/isIndexCodesVersionOf https://pure.iiasa.ac.at/id/document/87703 archive 353 disk0/00/01/59/37 2019-06-03 06:06:41 2021-08-27 17:31:50 2019-06-03 06:06:41 article show Birghila C. Pflug G. 1361 0000-0001-8215-3550 pub prog_risk Insurance contract optimization; Model error; Minimax solution; Distributional robustness We study the problem of optimal insurance contract design for risk management under a budget constraint. The contract holder takes into consideration that the loss distribution is not entirely known and therefore faces an ambiguity problem. For a given set of models, we formulate a minimax optimization problem of finding an optimal insurance contract that minimizes the distortion risk functional of the retained loss with premium limitation. We demonstrate that under the average value-at-risk measure, the entrance-excess of loss contracts are optimal under ambiguity, and we solve the distributionally robust optimal contract-design problem. It is assumed that the insurance premium is calculated according to a given baseline loss distribution and that the ambiguity set of possible distributions forms a neighborhood of the baseline distribution. To this end, we introduce a contorted Wasserstein distance. This distance is finer in the tails of the distributions compared to the usual Wasserstein distance. 2019-05-29 published Elsevier 10.1016/j.insmatheco.2019.05.005 229 public Insurance: Mathematics and Economics 88 30-43 TRUE 0167-6687 FALSE no info:eu-repo/semantics/article