Can Berk KALAYCI, Ökkeş ERTENLİCE, Hasan AKYER, Hakan AYGÖREN

Ortalama-varyans portföy optimizasyonunda genetik algoritma uygulamaları üzerine bir literatür araştırması

Markowitz’in ortaya koymuş olduğu ortalama-varyans portföy optimizasyonu, portföy yönetimi problemine temel bir cevap vermiştir. Bu model, getirinin en büyüklenmesi ve riskin en küçüklenmesi gibi iki çakışan amaç arasındaki en iyi ödünleşimi ile bir etkin sınır aramaktadır. Bir etkin sınır belirleme probleminin NP-Zor olduğu bilinmektedir. Problemin karmaşıklığı nedeniyle, giderek artan sayıda araştırmacı bu problemi çözmek için genetik algoritmaları kullanmışlardır. Bu çalışmada, mevcut literatürdeki genetik algoritmaların ortalama-varyans portföy optimizasyonu uygulamaları incelenmiştir. Çalışılmış olan problemlerin ana özellikleri ve önerilen genetik algoritma karakteristikleri özetlenmiştir.

Anahtar Kelimeler:

Portföy yönetimi ve optimizasyonu, Ortalama-varyans modeli, Evrimsel algoritmalar, Genetik algoritma

A review on the current applications of genetic algorithms in mean-variance portfolio optimization

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.

Keywords:

Portfolio management and optimization, Mean-variance model, Evolutionary algorithms, Genetic algorithm,

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