Building Fuzzy Autocorrelation Model and Its Application to the Analysis of Stock Price Time-Series Data

Yoshiyuki Yabuuchi, Junzo Watada

    研究成果: Chapter

    抄録

    The objective of economic analysis is to interpret the past, present or future economic state by analyzing economic data. Economic analyses are typically based on the time-series data or the cross-section data. Time-series analysis plays a pivotal role in analyzing time-series data. Nevertheless, economic systems are complex ones because they involve human behaviors and are affected by many factors. When a system includes substantial uncertainty, such as those concerning human behaviors, it is advantageous to employ a fuzzy system approach to such analysis. In this paper, we compare two fuzzy time-series models, namely a fuzzy autoregressive model proposed by Ozawa et al. and a fuzzy autocorrelation model proposed by Yabuuchi andWatada. Both models are built based on the concepts of fuzzy systems. In an analysis of the Nikkei Stock Average, we compare the effectiveness of the two models. Finally, we analyze tick-by-tick data of stock dealing by applying fuzzy autocorrelation model.

    元の言語English
    ホスト出版物のタイトルIntelligent Systems Reference Library
    ページ347-367
    ページ数21
    47
    DOI
    出版物ステータスPublished - 2013

    出版物シリーズ

    名前Intelligent Systems Reference Library
    47
    ISSN(印刷物)18684394
    ISSN(電子版)18684408

    Fingerprint

    Autocorrelation
    time series
    Time series
    Economics
    Fuzzy systems
    economics
    Time series analysis
    time series analysis
    Economic analysis
    economic system
    Time series data
    Stock prices
    uncertainty
    present
    Ticks
    Human behavior

    ASJC Scopus subject areas

    • Computer Science(all)
    • Information Systems and Management
    • Library and Information Sciences

    これを引用

    Yabuuchi, Y., & Watada, J. (2013). Building Fuzzy Autocorrelation Model and Its Application to the Analysis of Stock Price Time-Series Data. : Intelligent Systems Reference Library (巻 47, pp. 347-367). (Intelligent Systems Reference Library; 巻数 47). https://doi.org/10.1007/1007/978-3-642-33439-9_16

    Building Fuzzy Autocorrelation Model and Its Application to the Analysis of Stock Price Time-Series Data. / Yabuuchi, Yoshiyuki; Watada, Junzo.

    Intelligent Systems Reference Library. 巻 47 2013. p. 347-367 (Intelligent Systems Reference Library; 巻 47).

    研究成果: Chapter

    Yabuuchi, Y & Watada, J 2013, Building Fuzzy Autocorrelation Model and Its Application to the Analysis of Stock Price Time-Series Data. : Intelligent Systems Reference Library. 巻. 47, Intelligent Systems Reference Library, 巻. 47, pp. 347-367. https://doi.org/10.1007/1007/978-3-642-33439-9_16
    Yabuuchi Y, Watada J. Building Fuzzy Autocorrelation Model and Its Application to the Analysis of Stock Price Time-Series Data. : Intelligent Systems Reference Library. 巻 47. 2013. p. 347-367. (Intelligent Systems Reference Library). https://doi.org/10.1007/1007/978-3-642-33439-9_16
    Yabuuchi, Yoshiyuki ; Watada, Junzo. / Building Fuzzy Autocorrelation Model and Its Application to the Analysis of Stock Price Time-Series Data. Intelligent Systems Reference Library. 巻 47 2013. pp. 347-367 (Intelligent Systems Reference Library).
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