Risk assessment of a portfolio selection model based on a fuzzy statistical test

Pei Chun Lin, Junzo Watada, Berlin Wu

    Research output: Contribution to journalArticlepeer-review

    6 Citations (Scopus)


    The objective of our research is to build a statistical test that can evaluate different risks of a portfolio selection model with fuzzy data. The central points and radiuses of fuzzy numbers are used to determine the portfolio selection model, and we statistically evaluate the best return by a fuzzy statistical test. Empirical studies are presented to illustrate the risk evaluation of the portfolio selection model with interval values. We conclude that the fuzzy statistical test enables us to evaluate a stable expected return and low risk investment with different choices for k, which indicates the risk level. The results of numerical examples show that our method is suitable for short-term investments.

    Original languageEnglish
    Pages (from-to)579-588
    Number of pages10
    JournalIEICE Transactions on Information and Systems
    Issue number3
    Publication statusPublished - 2013 Mar


    • Data analysis
    • Fuzzy probability distributions
    • Fuzzy statistics
    • Optimization
    • Portfolio selection

    ASJC Scopus subject areas

    • Electrical and Electronic Engineering
    • Software
    • Artificial Intelligence
    • Hardware and Architecture
    • Computer Vision and Pattern Recognition


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