relation: https://pure.iiasa.ac.at/id/eprint/14272/
title: Incorporating model uncertainty into optimal insurance contract design
creator: Pflug, G.
creator: Timonina-Farkas, A.
creator: Hochrainer-Stigler, S.
description: In stochastic optimization models, the optimal solution heavily depends on the selected probability model for the scenarios. However, the scenario models are typically chosen on the basis of statistical estimates and are therefore subject to model error. We demonstrate here how the model uncertainty can be incorporated into the decision making process. We use a nonparametric approach for quantifying the model uncertainty and a minimax setup to find model-robust solutions. The method is illustrated by a risk management problem involving the optimal design of an insurance contract.
publisher: Elsevier
date: 2017-03-19
type: Article
type: PeerReviewed
format: text
language: en
rights: cc_by
identifier: https://pure.iiasa.ac.at/id/eprint/14272/1/Model_Ambiguity_Pre_Print.pdf
identifier:   Pflug, G. <https://pure.iiasa.ac.at/view/iiasa/229.html> ORCID: https://orcid.org/0000-0001-8215-3550 <https://orcid.org/0000-0001-8215-3550>, Timonina-Farkas, A., & Hochrainer-Stigler, S. <https://pure.iiasa.ac.at/view/iiasa/126.html>  (2017).  Incorporating model uncertainty into optimal insurance contract design.   Insurance: Mathematics and Economics 73 68-74. 10.1016/j.insmatheco.2016.11.008 <https://doi.org/10.1016/j.insmatheco.2016.11.008>.       
relation: 10.1016/j.insmatheco.2016.11.008
identifier: 10.1016/j.insmatheco.2016.11.008
doi: 10.1016/j.insmatheco.2016.11.008