Portfolio Optimization Using Three-Objective Particle Swarm Optimization

Asaad Alahrezaee (), Ali Falahati () and Kiomars Soheily ()
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Asaad Alahrezaee: Ph.D. Candidate in Economics, Razi University
Ali Falahati: Associate Professor of Economics, Razi University
Kiomars Soheily: Associate Professor of Economics, Razi University

Quarterly Journal of Applied Theories of Economics, 2019, vol. 5, issue 4, 31-52

Abstract: In optimizing the portfolio, the main issue is the optimal selection of assets that can be bought with a certain amount of money. Although risk minimizing and revenue maximizing on investment seems simple, but in practice several approaches have been proposed for an optimal portfolio. In 1950, Harry Marquitz introduced his model in which proposed the optimization of the asset basket as a quadratic programing model with the aim of minimizing the variance of the asset set, provided that the expected return equals a constant value. In this research, the problem of threeobjective optimization (i.e., maximizing stock returns, minimizing its risk and the third objective function, namely minimizing the number of assets) has been studied. Accordingly, investors, with admission a small amount of risk and a similar amount of return, will choose a basket of less assets. For this purpose, at first, genetic algorithms and multi- Particle Swarm Optimization algorithm were used to estimate the two-objective model of minimum variance and maximum return for better algorithm identification. Then, with regard to the better performance of the algorithm, this algorithm was used to estimate the three-objective model for maximizing stock returns, minimizing risk, and minimizing the number of assets

Keywords: Portfoloio optimization; Marquitz model; MOPSO algorithm; NSGA2 algorithm (search for similar items in EconPapers)
JEL-codes: C61 G11 G17 G21 (search for similar items in EconPapers)
Date: 2019
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