Fuzzy portfolio selection using genetic algorithm

  • Authors:
  • Rahib H. Abiyev;Mustafa Menekay

  • Affiliations:
  • Near East University, Department of Computer Engineering, Lefkosa, North Cyprus;Near East University, Department of Computer Information Systems, Lefkosa, North Cyprus

  • Venue:
  • Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special issue on intelligent systems for financial engineering and computational finance
  • Year:
  • 2007

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Abstract

This paper presents the development of fuzzy portfolio selection model in investment. Fuzzy logic is utilized in the estimation of expected return and risk. Using fuzzy logic, managers can extract useful information and estimate expected return by using not only statistical data, but also economical and financial behaviors of the companies and their business strategies. In the formulated fuzzy portfolio model, fuzzy set theory provides the possibility of trade-off between risk and return. This is obtained by assigning a satisfaction degree between criteria and constraints. Using the formulated fuzzy portfolio model, a Genetic Algorithm (GA) is applied to find optimal values of risky securities. Numerical examples are given to demonstrate the effectiveness of proposed method.