A linguistic-based portfolio selection model using weighted max-min operator and hybrid genetic algorithm

Authors:
Hossein Dastkhan;Naser Shams Gharneh;HamidReza Golmakani
Affiliations:
Industrial Engineering Department, AmirKabir University of Technology (Tehran Polytechnic), No. 15, Talime 5, Sajadeshomali Street, EmamShahr, Yazd, Iran;Industrial Engineering Department, AmirKabir University of Technology (Tehran Polytechnic), Hafez Street, Tehran, Iran;Industrial Engineering Department, University of Tafresh, Iran
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

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Abstract

Fuzzy mathematical programming is a main approach of multi-objective decision making, which prepares the decision makers to obtain the solution that satisfies his/her preference. In this paper, a fuzzy weighted max-min model for a mean-absolute deviation portfolio selection problem with real features is represented. To solve the resulted models, a hybrid genetic algorithm is proposed. An empirical study based on 75 assets of New York stock exchange (NYSE) is considered for in sample and out of sample analysis to illustrate the efficiency of the proposed model. The results show the high performance of fuzzy portfolios comparing with the performance of crisp portfolios and S&P 500 index.