NDLI: Portfolio optimization using multi-obj ective genetic algorithms

Content Provider	IEEE Xplore Digital Library
Author	Skolpadungket, P. Dahal, K. Harnpornchai, N.
Copyright Year	2007
Description	Author affiliation: Univ. of Bradford, Bradford (Skolpadungket, P.; Dahal, K.)
Abstract	A portfolio optimisation problem involves allocation of investment to a number of different assets to maximize yield and minimize risk in a given investment period. The selected assets in a portfolio not only collectively contribute to its yield but also interactively define its risk as usually measured by a portfolio variance. In this paper we apply various techniques of multiobjective genetic algorithms to solve portfolio optimization with some realistic constraints, namely cardinality constraints, floor constraints and round-lot constraints. The algorithms experimented in this paper are Vector Evaluated Genetic Algorithm (VEGA), Fuzzy VEGA, Multiobjective Optimization Genetic Algorithm (MOGA) , Strength Pareto Evolutionary Algorithm $2^{nd}$ version (SPEA2) and Non-Dominated Sorting Genetic Algorithm $2^{nd}$ version (NSGA2). The results show that using fuzzy logic to combine optimization objectives of VEGA (in VEGAFuzl) for this problem does improve performances measured by Generation Distance (GD) defined by average distances of the last generation of population to the nearest members of the true Pareto front but its solutions tend to cluster around a few points. MOGA and SPEA2 use some diversification algorithms and they perform better in terms of finding diverse solutions around Pareto front. SPEA2 performs the best even for comparatively small number of generations. NSGA2 performs closed to that of SPEA2 in GD but poor in distribution.
Starting Page	516
Ending Page	523
File Size	423136
Page Count	8
File Format	PDF
ISBN	9781424413393
DOI	10.1109/CEC.2007.4424514
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-09-25
Publisher Place	Singapore
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Portfolios Genetic algorithms Investments Pareto optimization Asset management Constraint optimization Evolutionary computation Sorting Fuzzy logic Performance evaluation Fuzzy VEGA Portfolio optimisation Investment management Multiobjective Genetic Algorithms Vector Evaluated Genetic Algorithm VEGA Strength Pareto Evolutionary Algorithm SPEA2
Content Type	Text
Resource Type	Article

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