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 languageEnglish
    Pages (from-to)5935-5944
    Number of pages10
    JournalInternational Journal of Innovative Computing, Information and Control
    Volume8
    Issue number8
    Publication statusPublished - 2012 Aug

    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

    Fingerprint Dive into the research topics of 'Portfolio selection model with interval values based on fuzzy probability distribution functions'. Together they form a unique fingerprint.

  • Cite this