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Journal of Artificial Intelligence and Soft Computing Research

The Journal of Polish Neural Network Society, the University of Social Sciences in Lodz & Czestochowa University of Technology

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Influence Of Membership Function’s Shape On Portfolio Optimization Results

Aleksandra Rutkowska
  • Department of Applied Mathematics Poznan University of Economics and Business al. Niepodleglosci, 61-875 Poznan, Poland
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2016-01-13 | DOI: https://doi.org/10.1515/jaiscr-2016-0005


Portfolio optimization, one of the most rapidly growing field of modern finance, is selection process, by which investor chooses the proportion of different securities and other assets to held. This paper studies the influence of membership function’s shape on the result of fuzzy portfolio optimization and focused on portfolio selection problem based on credibility measure. Four different shapes of the membership function are examined in the context of the most popular optimization problems: mean-variance, mean-semivariance, entropy minimization, value-at-risk minimization. The analysis takes into account both: the study of necessary and sufficient conditions for the existence of extremes, as well as the statistical inference about the differences based on simulation.

Keywords: fuzzy variable; membership function; fuzzy portfolio optimization


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About the article

Published Online: 2016-01-13

Published in Print: 2016-01-01

Citation Information: Journal of Artificial Intelligence and Soft Computing Research, Volume 6, Issue 1, Pages 45–54, ISSN (Online) 2083-2567, DOI: https://doi.org/10.1515/jaiscr-2016-0005.

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© 2016 Academy of Management (SWSPiZ), Lodz. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0

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