Author/Authors
kalayci, can berk pamukkale university - college of engineering - department of industrial engineering, Denizli, Turkey , ertenlice, okkes pamukkale university - faculty of engineering - department of industrial engineering, Denizli, Turkey , akyer, hasan pamukkale university - faculty of engineering - department of industrial engineering, Denizli, Turkey , aygoren, hakan pamukkale university - faculty of economics and administrative sciences - department of business administration, Denizli, Turkey
Title Of Article
A review on the current applications of genetic algorithms in mean-variance portfolio optimization
شماره ركورد
40935
Abstract
Mean-variance portfolio optimization model, introduced by Markowitz, provides a fundamental answer to the problem of portfolio management. This model seeks an efficient frontier with the best trade-offs between two conflicting objectives of maximizing return and minimizing risk. The problem of determining an efficient frontier is known to be NP-hard. Due to the complexity of the problem, genetic algorithms have been widely employed by a growing number of researchers to solve this problem. In this study, a literature review of genetic algorithms implementations on mean-variance portfolio optimization is examined from the recent published literature. Main specifications of the problems studied and the specifications of suggested genetic algorithms have been summarized.
From Page
470
NaturalLanguageKeyword
Portfolio management and optimization , Mean , variance model , Evolutionary algorithms , Genetic algorithm
JournalTitle
Pamukkale University Journal Of Engineering Sciences
To Page
476
JournalTitle
Pamukkale University Journal Of Engineering Sciences
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