Portfolio selection model with interval values based on fuzzy probability distribution functions

Pei Chun Lin, Junzo Watada, Berlin Wu

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

In order to analyze uncertain phenomena in real world, the concept of fuzzy random variables is widely employed in model building. In dealing with fuzzy data, defuzzification plays a central role. In this paper, portfolio selection problems are dealt as interval values. We calculate the expected values, variance and covariance by using the estimated parameters of underlying probability distribution function. The estimated values enable us to build up a portfolio selection model with estimated parameters on the basic of Markowitz's mean-variance model. The result exemplified that we have different choices of k which can decide the best expected return and less risk level in our model, also that we can provide not only one choice of portfolio selection but also two or more for decision makers.

Original language English 5935-5944 10 International Journal of Innovative Computing, Information and Control 8 8 Published - 2012 Aug

Fingerprint

Fuzzy Probability
Selection Model
Portfolio Selection
Probability Distribution Function
Probability distributions
Distribution functions
Interval
Fuzzy Random Variable
Defuzzification
Fuzzy Data
Expected Value
Random variables
Calculate
Model

Keywords

• Fuzzy probability distributions
• Fuzzy statistics and data analysis
• Optimization
• Portfolio selection

ASJC Scopus subject areas

• Computational Theory and Mathematics
• Information Systems
• Software
• Theoretical Computer Science

Cite this

Portfolio selection model with interval values based on fuzzy probability distribution functions. / Lin, Pei Chun; Watada, Junzo; Wu, Berlin.

In: International Journal of Innovative Computing, Information and Control, Vol. 8, No. 8, 08.2012, p. 5935-5944.

Research output: Contribution to journalArticle

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