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Kaucic, Massimiliano
Daris, Roberto
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[Journal:] Risks [ISSN:] 2227-9091 [Volume:] 3 [Year:] 2015 [Issue:] 3 [Pages:] 390-419
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.
multi-objective stochastic programming
performance indicators
chance constraint
normal constraint method
non-life insurance company
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