Comparative evaluation of fuzzy logic and genetic algorithms models for portfolio optimization
| Autor: | Gholamreza Farsad Amanollahi, Heidar Masoumi Soureh |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
0209 industrial biotechnology
Mathematical optimization Computer science lcsh:HF5735-5746 Quality control and genetic algorithms 02 engineering and technology Genetic algorithms lcsh:Business records management General Business Management and Accounting Fuzzy logic Comparative evaluation 020901 industrial engineering & automation 0202 electrical engineering electronic engineering information engineering Portfolio 020201 artificial intelligence & image processing Portfolio optimization Profits optimization Selection (genetic algorithm) |
| Zdroj: | Management Science Letters, Vol 7, Iss 5, Pp 247-254 (2017) |
| ISSN: | 1923-9343 1923-9335 |
| Popis: | Selection of optimum methods which have appropriate speed and precision for planning and de-cision-making has always been a challenge for investors and managers. One the most important concerns for them is investment planning and optimization for acquisition of desirable wealth under controlled risk with the best return. This paper proposes a model based on Markowitz the-orem by considering the aforementioned limitations in order to help effective decisions-making for portfolio selection. Then, the model is investigated by fuzzy logic and genetic algorithms, for the optimization of the portfolio in selected active companies listed in Tehran Stock Exchange over the period 2012-2016 and the results of the above models are discussed. The results show that the two studied models had functional differences in portfolio optimization, its tools and the possibility of supplementing each other and their selection. |
| Databáze: | OpenAIRE |
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