Decision making of a portfolio selection model based on fuzzy statistic test

Pei Chun Lin, Junzo Watada, Berlin Wu

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    The objective of our research is to build a statistical test that can evaluate the sensitivity of a portfolio selection model with fuzzy data. The central point and radius are used to determine the portfolio selection model and we make a decision for the best return by a fuzzy statistical test. Empirical studies are presented to illustrate the risk of the portfolio selection model with interval values. We conclude that the evaluation by the fuzzy statistical test enables us to obtain a stable expected return and low risk investment with different choices based on the risk level k, which is taken for the risk level.

    Original languageEnglish
    Title of host publication6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012
    Pages1931-1937
    Number of pages7
    DOIs
    Publication statusPublished - 2012
    Event2012 Joint 6th International Conference on Soft Computing and Intelligent Systems, SCIS 2012 and 13th International Symposium on Advanced Intelligence Systems, ISIS 2012 - Kobe, Japan
    Duration: 2012 Nov 202012 Nov 24

    Other

    Other2012 Joint 6th International Conference on Soft Computing and Intelligent Systems, SCIS 2012 and 13th International Symposium on Advanced Intelligence Systems, ISIS 2012
    CountryJapan
    CityKobe
    Period12/11/2012/11/24

    Keywords

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

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Software

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  • Cite this

    Lin, P. C., Watada, J., & Wu, B. (2012). Decision making of a portfolio selection model based on fuzzy statistic test. In 6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012 (pp. 1931-1937). [6505076] https://doi.org/10.1109/SCIS-ISIS.2012.6505076