Abstract
In this paper fuzzy mean-entropy-skewness models are proposed for optimal portfolio selection. Entropy is favored as a measure of risk as it is free from dependence on symmetric probability distribution. Credibility theory is applied to evaluate fuzzy mean, skewness and entropy. Hybrid intelligence algorithm is used for simulation. Numerical examples are given in favor of each of the models.
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Bhattacharyya, R., Kar, M.B., Kar, S., Majumder, D.D. (2009). Mean-Entropy-Skewness Fuzzy Portfolio Selection by Credibility Theory Approach. In: Chaudhury, S., Mitra, S., Murthy, C.A., Sastry, P.S., Pal, S.K. (eds) Pattern Recognition and Machine Intelligence. PReMI 2009. Lecture Notes in Computer Science, vol 5909. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11164-8_98
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DOI: https://doi.org/10.1007/978-3-642-11164-8_98
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