Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/167858
Authors: 
Kaucic, Massimiliano
Daris, Roberto
Year of Publication: 
2015
Citation: 
[Journal:] Risks [ISSN:] 2227-9091 [Volume:] 3 [Year:] 2015 [Issue:] 3 [Pages:] 390-419
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.
Subjects: 
multi-objective stochastic programming
performance indicators
chance constraint
normal constraint method
non-life insurance company
Persistent Identifier of the first edition: 
Creative Commons License: 
http://creativecommons.org/licenses/by/4.0/
Document Type: 
Article
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