Metaheuristics in combinatorial optimization: Overview and conceptual comparison
ACM Computing Surveys (CSUR)
Biologically Inspired Algorithms for Financial Modelling (Natural Computing Series)
Biologically Inspired Algorithms for Financial Modelling (Natural Computing Series)
Hybrid search for cardinality constrained portfolio optimization
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Portfolio Management with Heuristic Optimization (Advances in Computational Management Science)
Portfolio Management with Heuristic Optimization (Advances in Computational Management Science)
A multi-objective approach to integrated risk management
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part III
A tree-based GA representation for the portfolio optimization problem
Proceedings of the 10th annual conference on Genetic and evolutionary computation
A cross-entropy method for value-at-risk constrained optimization
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part II
Money in trees: How memes, trees, and isolation can optimize financial portfolios
Information Sciences: an International Journal
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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.