Optimum portfolio selection using a hybrid genetic algorithm and analytic hierarchy process

Maghsoud Solimanpur, Gholamreza Mansourfar and Farzad Ghayour

Studies in Economics and Finance, 2015, vol. 32, issue 3, 379-394

Abstract: Purpose - – The purpose of this paper is to present a multi-objective model to the optimum portfolio selection using genetic algorithm and analytic hierarchy process (AHP). Portfolio selection is a multi-objective decision-making problem in financial management. Design/methodology/approach - – The proposed approach solves the problem in two stages. In the first stage, the portfolio selection problem is formulated as a zero-one mathematical programming model to optimize two objectives, namely, return and risk. A genetic algorithm (GA) with multiple fitness functions called as Multiple Fitness Functions Genetic Algorithm is applied to solve the formulated model. The proposed GA results in several non-dominated portfolios being in the Pareto (efficient) frontier. A decision-making approach based on AHP is then used in the second stage to select the portfolio from among the solutions obtained by GA which satisfies a decision-maker’s interests at most. Findings - – The proposed decision-making system enables an investor to find a portfolio which suits for his/her expectations at most. The main advantage of the proposed method is to provide prima-facie information about the optimal portfolios lying on the efficient frontier and thus helps investors to decide the appropriate investment alternatives. Originality/value - – The value of the paper is due to its comprehensiveness in which seven criteria are taken into account in the selection of a portfolio including return, risk, beta ratio, liquidity ratio, reward to variability ratio, Treynor’s ratio and Jensen’s alpha.

Keywords: Genetic algorithm; Analytic hierarchy process; Portfolio selection; G11 (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eme:sefpps:v:32:y:2015:i:3:p:379-394

DOI: 10.1108/SEF-08-2012-0085

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