Author/Authors
akyer, hasan pamukkale üniversitesi - mühendislik fakültesi - endüstri mühendisliği bölümü, Denizli, Turkey , kalayci, can berk pamukkale üniversitesi - mühendislik fakültesi - endüstri mühendisliği bölümü, Denizli, Turkey , aygören, hakan pamukkale üniversitesi - iktisadi ve idari bilimler fakültesi - işletme bölümü, Denizli, Turkey
Title Of Article
Particle swarm optimization algorithm for mean-variance portfolio optimization: A case study of Istanbul Stock Exchange
شماره ركورد
41032
Abstract
While investors used to create their portfolios according to traditional portfolio theory in the past, today modern portfolio approach is widely preferred. The basis of the modern portfolio theory was suggested by Harry Markowitz with the mean variance model. A greater number of securities in a portfolio is difficult to manage and has an increased transaction cost. Therefore, the number of securities in the portfolio should be restricted. The problem of portfolio optimization with cardinality constraints is NP-Hard. Meta-heuristic methods are generally preferred to solve since problems in this class are difficult to be solved with exact solution algorithms within acceptable times. In this study, a particle swarm optimization algorithm has been adapted to solve the portfolio optimization problem and applied to Istanbul Stock Exchange. The experiments show that while in low risk levels it is required to invest into more number of assets in order to converge unconstrained efficient frontier, as risk level increases the number of assets to be held is decreased.
From Page
124
NaturalLanguageKeyword
Portfolio optimization , Mean , variance model , Heuristic methods , Particle swarm optimization
JournalTitle
Pamukkale University Journal Of Engineering Sciences
To Page
129
JournalTitle
Pamukkale University Journal Of Engineering Sciences
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