Solving a portfolio optimisation problem via heuristic algorithms Online publication date: Mon, 19-Oct-2015
by Xin-Yao Song; Can Cui; Xiao-Shuang Chen; Qi Kang
International Journal of Wireless and Mobile Computing (IJWMC), Vol. 9, No. 2, 2015
Abstract: Portfolio investment has become a fashionable investment with the advantage of risk dispersion. In this work, we examine the ability of three heuristic algorithms to distribute capital associated with the standard mean-variance portfolio optimisation with different risks as constraints. Penalty function is used to deal with the constraint conditions. The three methods considered are Differential Evolution (DE), Comprehensive Learning Particle Swarm Optimiser (CLPSO) and Covariance Matrix Adaption Evolution Strategy (CMA-ES). The results demonstrate that CMA-ES is superior in solving investment portfolio problems in comparison to the other two heuristic algorithms.
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