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

Meng Yuan, Junzo Watada

    研究成果: Conference contribution

    1 被引用数 (Scopus)

    抄録

    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.

    本文言語English
    ホスト出版物のタイトルIEEE International Conference on Fuzzy Systems
    出版社Institute of Electrical and Electronics Engineers Inc.
    ページ2047-2054
    ページ数8
    ISBN(印刷版)9781479920723
    DOI
    出版ステータスPublished - 2014 9 4
    イベント2014 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2014 - Beijing
    継続期間: 2014 7 62014 7 11

    Other

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

    ASJC Scopus subject areas

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

    フィンガープリント 「A minimax model of portfolio optimization using data mining to predict interval return rate」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

    引用スタイル