Particle Swarm Optimization (PSO) for the constrained portfolio optimization problem

Hanhong Zhu, Yi Wang, Kesheng Wang, Yun Chen

    Research output: Contribution to journalArticlepeer-review

    Abstract

    One of the most studied problems in the financial investment expert system is the intractability of portfolios. The non-linear constrained portfolio optimization problem with multi-objective functions cannot be efficiently solved using traditionally approaches. This paper presents a meta-heuristic approach to portfolio optimization problem using Particle Swarm Optimization (PSO) technique. The model is tested on various restricted and unrestricted risky investment portfolios and a comparative study with Genetic Algorithms is implemented. The PSO model demonstrates high computational efficiency in constructing optimal risky portfolios. Preliminary results show that the approach is very promising and achieves results comparable or superior with the state of the art solvers. © 2011 Published by Elsevier Ltd.
    Original languageEnglish
    Pages (from-to)10161-10169
    Number of pages8
    JournalExpert Systems with Applications
    Volume38
    Issue number8
    DOIs
    Publication statusPublished - Aug 2011

    Keywords

    • Expert system
    • Optimal portfolio
    • Particle Swarm Optimization (PSO)
    • Portfolio management (PM)
    • Sharp Ratio (SR)
    • Swarm Intelligence (SI)

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