Influence Of Membership Function’s Shape On Portfolio Optimization Results

Abstract 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.

[1]  Baoding Liu,et al.  Entropy of Credibility Distributions for Fuzzy Variables , 2008, IEEE Transactions on Fuzzy Systems.

[2]  Jin Peng Measuring Fuzzy Risk by Credibilistic Value at Risk , 2008, 2008 3rd International Conference on Innovative Computing Information and Control.

[3]  Petia D. Koprinkova-Hristova Membership Functions Shape and its Influence on the Dynamical Behaviour of Fuzzy Logic Controller , 2000, Cybern. Syst..

[4]  Xiaoxia Huang,et al.  Portfolio Analysis - From Probabilistic to Credibilistic and Uncertain Approaches , 2012, Studies in Fuzziness and Soft Computing.

[5]  Xiaoxia Huang,et al.  Mean-Entropy Models for Fuzzy Portfolio Selection , 2008, IEEE Transactions on Fuzzy Systems.

[6]  Jing Ren,et al.  Fuzzy logic (FL) controlled HVDC system-influence of shape, width & distribution of membership functions (MFs) , 2010, CCECE 2010.

[7]  Xiang Li,et al.  Mean-variance-skewness model for portfolio selection with fuzzy returns , 2010, Eur. J. Oper. Res..

[8]  Xiaoxia Huang,et al.  Mean-semivariance models for fuzzy portfolio selection , 2008 .

[9]  M. Kazerani,et al.  Investigation of Membership Function Shapes in a Fuzzy-Controlled HVDC System , 2006, 2006 IEEE International Symposium on Industrial Electronics.

[10]  Xiaoxia Huang,et al.  Fuzzy chance-constrained portfolio selection , 2006, Appl. Math. Comput..

[11]  F. Wilcoxon Individual Comparisons by Ranking Methods , 1945 .

[12]  Witold Pedrycz,et al.  Value-at-Risk-Based Two-Stage Fuzzy Facility Location Problems , 2009, IEEE Transactions on Industrial Informatics.

[13]  Xiaoxia Huang,et al.  Minimax mean-variance models for fuzzy portfolio selection , 2011, Soft Comput..

[14]  Baoding Liu,et al.  Uncertainty Theory - A Branch of Mathematics for Modeling Human Uncertainty , 2011, Studies in Computational Intelligence.

[15]  Yian-Kui Liu,et al.  Expected value of fuzzy variable and fuzzy expected value models , 2002, IEEE Trans. Fuzzy Syst..

[16]  Jin Peng,et al.  Credibility programming approach to fuzzy portfolio selection problems , 2005, 2005 International Conference on Machine Learning and Cybernetics.