TY - JOUR
ID - 8079
TI - Portfolio Optimization Using Three-Objective Particle Swarm Optimization
JO - Quarterly Journal of Applied Theories of Economics
JA - ECOJ
LA - en
SN -
AU - Alahrezaee, Asaad
AU - Falahati, Ali
AU - Sohaili, Kiomars
AD - Ph.D. Candidate in Economics, Razi University
AD - Associate Professor of Economics, Razi University
Y1 - 2019
PY - 2019
VL - 5
IS - 4
SP - 31
EP - 52
KW - Portfoloio Optimization
KW - Marquitz Model
KW - MOPSO Algorithm
KW - NSGA2 Algorithm
DO -
N2 - 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 three-objective 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.
UR - https://ecoj.tabrizu.ac.ir/article_8079.html
L1 - https://ecoj.tabrizu.ac.ir/article_8079_ea07a01c908401a7196c5034333ae957.pdf
ER -