Stochastic Optimization Models of Actuarial Mathematics

Ermoliev YM, Norkin VI, & Norkin BV (2020). Stochastic Optimization Models of Actuarial Mathematics. Cybernetics and Systems Analysis DOI:10.1007/s10559-020-00221-0. (In Press)

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Abstract

The paper overviews stochastic optimization models of actuarial mathematics and methods for their solution from the point of view of the methodology of multicriteria stochastic programming and optimal control. The evolution of the capital of an insurance company is considered in discrete time. The main random parameters of the models are insurance payouts, i.e., the ratios of paid insurance claims to the corresponding premiums per unit time. Optimization variables are the structure of the insurance portfolio (gross premium structure) and amount of dividends. As efficiency criteria, indicators of the profitability of the insurance business are used, and, as risk indicators the ruin probability and the recourse capital necessary to prevent the ruin are taken. The goal of the optimization is to find Pareto-optimal solutions. Methods for finding these solutions are proposed.

Item Type: Article
Uncontrolled Keywords: actuarial mathematics; multicriteria problems; probability constraints; risk process; ruin probability; stochastic optimal control; stochastic programming; two-stage problems
Depositing User: Luke Kirwan
Date Deposited: 17 Feb 2020 08:06
Last Modified: 17 Feb 2020 08:06
URI: http://pure.iiasa.ac.at/16296

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