Optimal Portfolio Prediction in Tehran Stock Market using Multi-Objective Evolutionary Algorithms, NSGA-II and MOPSO

Optimal Portfolio Prediction in Tehran Stock Market using Multi-Objective Evolutionary Algorithms, NSGA-II and MOPSO

Despite the growing use of evolutionary multi-objective optimization algorithms in different categories of science, these algorithms as a powerful tool in portfolio optimization and specially solving multi-objective portfolio optimization problem is still in its early stages. In this paper, MOEAs ha...

Bibliografski detalji
Glavni autori:	Mahsa Rajabi, Hamid Khaloozadeh
Format:	Članak
Jezik:	fas
Izdano:	University of Tehran 2014-09-01
Serija:	تحقیقات مالی
Teme:	optimal portfolio prediction multi-objective evolutionary algorithms conditional value at risk nsga-ii mopso
Online pristup:	https://jfr.ut.ac.ir/article_50715_585cb96acf8f5ee88526fdd187a14bd5.pdf

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