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Multi-Objective Stochastic Optimization Programs for a Non-Life Insurance Company under Solvency Constraints

Author

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  • Massimiliano Kaucic

    (Department of Economics, Business, Mathematics and Statistics, University of Trieste, Piazzale Europa 1, 34127 Trieste, Italy)

  • Roberto Daris

    (Department of Economics, Business, Mathematics and Statistics, University of Trieste, Piazzale Europa 1, 34127 Trieste, Italy)

Abstract

In the paper, we introduce a multi-objective scenario-based optimization approach for chance-constrained portfolio selection problems. More specifically, a modified version of the normal constraint method is implemented with a global solver in order to generate a dotted approximation of the Pareto frontier for bi- and tri-objective programming problems. Numerical experiments are carried out on a set of portfolios to be optimized for an EU-based non-life insurance company. Both performance indicators and risk measures are managed as objectives. Results show that this procedure is effective and readily applicable to achieve suitable risk-reward tradeoff analysis.

Suggested Citation

  • Massimiliano Kaucic & Roberto Daris, 2015. "Multi-Objective Stochastic Optimization Programs for a Non-Life Insurance Company under Solvency Constraints," Risks, MDPI, vol. 3(3), pages 1-30, September.
    • Handle: RePEc:gam:jrisks:v:3:y:2015:i:3:p:390-419:d:55820
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    References listed on IDEAS

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    1. Alessandro Staino & Emilio Russo & Massimo Costabile & Arturo Leccadito, 2023. "Minimum capital requirement and portfolio allocation for non-life insurance: a semiparametric model with Conditional Value-at-Risk (CVaR) constraint," Computational Management Science, Springer, vol. 20(1), pages 1-32, December.

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