Abstract
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.
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Chen, Y., Liu, YK., Chen, J. (2006). Fuzzy Portfolio Selection Problems Based on Credibility Theory. In: Yeung, D.S., Liu, ZQ., Wang, XZ., Yan, H. (eds) Advances in Machine Learning and Cybernetics. Lecture Notes in Computer Science(), vol 3930. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11739685_40
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DOI: https://doi.org/10.1007/11739685_40
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33584-9
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