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A hybrid particle swarm optimization approach and its application to solving portfolio selection problems

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Bibliographic Details
Main Authors: Shamshul Bahar, Yaakob, Prof. Madya, Watada, Junzo
Other Authors: shamshul@fuji.waseda.jp
Format: Article
Language:English
Published: Fuji Technology Press 2011
Subjects:
Genetic algorithm
Hybrid particle swarm optimization
Modern portfolio theory
Particle swarm optimization
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/14027
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id my.unimap-14027
record_format dspace
spelling my.unimap-140272011-10-05T05:08:31Z A hybrid particle swarm optimization approach and its application to solving portfolio selection problems Shamshul Bahar, Yaakob, Prof. Madya Watada, Junzo shamshul@fuji.waseda.jp Genetic algorithm Hybrid particle swarm optimization Modern portfolio theory Particle swarm optimization Link to publisher's homepage at http://www.fujipress.jp/ In modern portfolio theory, the basic topic is how to construct a diversified portfolio of financial securities to improve trade-offs between risk and return. The objective of this paper is to apply a heuristic algorithm using Particle Swarm Optimization (PSO) to the portfolio selection problem. PSO makes the search algorithm efficient by combining a local search method through self-experience with the global search method through neighboring experience. PSO attempts to balance the exploration-exploitation tradeoff that achieves efficiency and accuracy of optimization. In this paper, a newly obtained approach is proposed by making simple modifications to the standard PSO: the velocity is controlled and the mutation operator of Genetic Algorithms (GA) is added to solve a stagnation problem. Our adaptation and implementation of the PSO search strategy are applied to portfolio selection. Results of typical applications demonstrate that the Velocity Control Hybrid PSO (VC-HPSO) proposed in this study effectively finds optimum solution to portfolio selection problems. Results also show that our proposedmethod is a viable approach to portfolio selection. 2011-10-05T05:08:31Z 2011-10-05T05:08:31Z 2011-06 Article Journal of Advanced Computational Intelligence and Intelligent Informatics, vol. 15 (4), 2011, pages 473-478 1343-0130 http://www.fujipress.jp/finder/xslt.php?mode=present&inputfile=JACII001500040011.xml http://hdl.handle.net/123456789/14027 en Fuji Technology Press
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Genetic algorithm
Hybrid particle swarm optimization
Modern portfolio theory
Particle swarm optimization
spellingShingle Genetic algorithm
Hybrid particle swarm optimization
Modern portfolio theory
Particle swarm optimization
Shamshul Bahar, Yaakob, Prof. Madya
Watada, Junzo
A hybrid particle swarm optimization approach and its application to solving portfolio selection problems
description Link to publisher's homepage at http://www.fujipress.jp/
author2 shamshul@fuji.waseda.jp
author_facet shamshul@fuji.waseda.jp
Shamshul Bahar, Yaakob, Prof. Madya
Watada, Junzo
format Article
author Shamshul Bahar, Yaakob, Prof. Madya
Watada, Junzo
author_sort Shamshul Bahar, Yaakob, Prof. Madya
title A hybrid particle swarm optimization approach and its application to solving portfolio selection problems
title_short A hybrid particle swarm optimization approach and its application to solving portfolio selection problems
title_full A hybrid particle swarm optimization approach and its application to solving portfolio selection problems
title_fullStr A hybrid particle swarm optimization approach and its application to solving portfolio selection problems
title_full_unstemmed A hybrid particle swarm optimization approach and its application to solving portfolio selection problems
title_sort hybrid particle swarm optimization approach and its application to solving portfolio selection problems
publisher Fuji Technology Press
publishDate 2011
url http://dspace.unimap.edu.my/xmlui/handle/123456789/14027
_version_ 1643790856724938752
score 13.214268

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