Fuzzy Portfolio Selection Problems Based on Credibility Theory

  • Yanju Chen
  • Yan-Kui Liu
  • Junfen Chen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3930)


We first deduce the variance formulas of normal, triangular and trapezoidal fuzzy variables in credibility theory. Then two classes of fuzzy portfolio selection models are built based on credibility measure, the expected value and variance of a fuzzy variable. To solve the proposed models, a genetic algorithm is employed. Finally, two numerical examples are provided for the proposed portfolio selection models to test the designed algorithm.


Genetic Algorithm Return Rate Portfolio Selection Fuzzy Variable Possibility Distribution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yanju Chen
    • 1
  • Yan-Kui Liu
    • 1
  • Junfen Chen
    • 1
  1. 1.College of Mathematics and Computer ScienceHebei UniversityBaodingChina

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