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
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.
NaturalLanguageKeyword :
Portfolio management and optimization , Mean , variance model , Evolutionary algorithms , Genetic algorithm
