Building a fuzzy multi-objective portfolio selection model with distinct risk measurements

You Li, Bo Wang, Junzo Watada

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

    5 Citations (Scopus)

    Abstract

    Based on portfolio selection theory, this study proposes an improved fuzzy multi-objective model that can evaluate the invest risk exactly and increase the probability of obtaining the expected return. In building the model, fuzzy Value-at-Risk (VaR) is used to evaluate the exact future risk, in term of loss. The VaR can directly reflect the greatest loss of a selection case under a given confidence level. On the other hand, variance is utilized to make the selection more stable. This model can provide investors with more significant information in decision-making. To better solve this model, an improved particle swarm optimization algorithm is designed to mitigate the conventional local convergence problem. Finally, the proposed model and algorithm are exemplified by some numerical examples. Experiment results show that the model and algorithm are effective in solving the multi-objective portfolio selection problem.

    Original languageEnglish
    Title of host publicationIEEE International Conference on Fuzzy Systems
    Pages1096-1102
    Number of pages7
    DOIs
    Publication statusPublished - 2011
    Event2011 IEEE International Conference on Fuzzy Systems, FUZZ 2011 - Taipei
    Duration: 2011 Jun 272011 Jun 30

    Other

    Other2011 IEEE International Conference on Fuzzy Systems, FUZZ 2011
    CityTaipei
    Period11/6/2711/6/30

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    Keywords

    • Fuzzy multi-objective portfolio selection model
    • fuzzy simulation
    • fuzzy Value-at-Risk
    • fuzzy variable
    • improved particle swarm optimization

    ASJC Scopus subject areas

    • Software
    • Artificial Intelligence
    • Applied Mathematics
    • Theoretical Computer Science

    Cite this

    Li, Y., Wang, B., & Watada, J. (2011). Building a fuzzy multi-objective portfolio selection model with distinct risk measurements. In IEEE International Conference on Fuzzy Systems (pp. 1096-1102). [6007314] https://doi.org/10.1109/FUZZY.2011.6007314