A minimax model of portfolio optimization using data mining to predict interval return rate

Meng Yuan, Junzo Watada

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

    1 Citation (Scopus)

    Abstract

    In 1950s, Markowitzs first proposed portfolio theory based on a mean-variance (MV) model to balance the risk and profit of decentralized investment. The two main inputs of MV are expected return rate and the variance of expected return rate. The expected return rate is an estimated value which is often decided by experts. Various uncertainty of stock price brings difficulties to predict return rate even for experts. MV model has its tendency to maximize the influence of errors in the input assumptions. Some scholars used fuzzy intervals to describe the return rate. However, there were still some variables decided by experts. This paper proposes a classification method to find the latent relationship between the interval return rate and the trading data of a stock and predict the interval of return rate without consulting any expert. Then this paper constructs the portfolio model based on minimax rule with interval numbers. The evaluation results show that the proposed method is reliable.

    Original languageEnglish
    Title of host publicationIEEE International Conference on Fuzzy Systems
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages2047-2054
    Number of pages8
    ISBN (Print)9781479920723
    DOIs
    Publication statusPublished - 2014 Sep 4
    Event2014 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2014 - Beijing
    Duration: 2014 Jul 62014 Jul 11

    Other

    Other2014 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2014
    CityBeijing
    Period14/7/614/7/11

    Fingerprint

    Portfolio Optimization
    Minimax
    Data mining
    Data Mining
    Predict
    Interval
    Portfolio Theory
    Fuzzy Intervals
    Interval number
    Profitability
    Stock Prices
    Model
    Decentralized
    Profit
    Maximise
    Model-based
    Uncertainty
    Evaluation

    Keywords

    • Classification
    • Interval number
    • Minimax
    • Portfolio

    ASJC Scopus subject areas

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

    Cite this

    Yuan, M., & Watada, J. (2014). A minimax model of portfolio optimization using data mining to predict interval return rate. In IEEE International Conference on Fuzzy Systems (pp. 2047-2054). [6891693] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/FUZZ-IEEE.2014.6891693

    A minimax model of portfolio optimization using data mining to predict interval return rate. / Yuan, Meng; Watada, Junzo.

    IEEE International Conference on Fuzzy Systems. Institute of Electrical and Electronics Engineers Inc., 2014. p. 2047-2054 6891693.

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

    Yuan, M & Watada, J 2014, A minimax model of portfolio optimization using data mining to predict interval return rate. in IEEE International Conference on Fuzzy Systems., 6891693, Institute of Electrical and Electronics Engineers Inc., pp. 2047-2054, 2014 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2014, Beijing, 14/7/6. https://doi.org/10.1109/FUZZ-IEEE.2014.6891693
    Yuan M, Watada J. A minimax model of portfolio optimization using data mining to predict interval return rate. In IEEE International Conference on Fuzzy Systems. Institute of Electrical and Electronics Engineers Inc. 2014. p. 2047-2054. 6891693 https://doi.org/10.1109/FUZZ-IEEE.2014.6891693
    Yuan, Meng ; Watada, Junzo. / A minimax model of portfolio optimization using data mining to predict interval return rate. IEEE International Conference on Fuzzy Systems. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 2047-2054
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