An evolutionary computation approach to scenario-based risk-return portfolio optimization for general risk measures

Publication: Scientific journalJournal articlepeer-review


Due to increasing complexity and non-convexity of financial engineering problems, biologically inspired heuristic algorithms gained significant importance especially in the area of financial decision optimization. In this paper, the stochastic scenario-based risk-return portfolio optimization problem is analyzed and solved with an evolutionary computation approach. The advantage of applying this approach is the creation of a common framework for an arbitrary set of loss distribution-based risk measures, regardless of their underlying structure. Numerical results for three of the most commonly used risk measures conclude the paper.
Original languageEnglish
Pages (from-to)199 - 207
JournalLecture Notes in Computer Science (LNCS)
Publication statusPublished - 1 Nov 2007

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