Rough sets based prediction model of tick-wise price fluctuations

Yoshiyuki Matsumoto, Junzo Watada

    Research output: Contribution to journalArticle

    1 Citation (Scopus)

    Abstract

    Rough sets theory was proposed by Z. Pawlak in 1982. This theory enables us to mine knowledge granules through a decision rule from a database, a web base, a set and so on. We can apply the decision rule to reason, estimate, evaluate, or forecast unknown objects. In this paper, the rough set model is used to analyze of time series data of tick-wise price fluctuation, whereknowledge granules are mined from the data set of tick-wise price fluctuations.

    Original languageEnglish
    Pages (from-to)449-453
    Number of pages5
    JournalJournal of Advanced Computational Intelligence and Intelligent Informatics
    Volume15
    Issue number4
    Publication statusPublished - 2011 Jun

    Fingerprint

    Rough set theory
    Time series

    Keywords

    • Rough sets
    • Tick-wise price
    • Time-series data

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Computer Vision and Pattern Recognition
    • Human-Computer Interaction

    Cite this

    Rough sets based prediction model of tick-wise price fluctuations. / Matsumoto, Yoshiyuki; Watada, Junzo.

    In: Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol. 15, No. 4, 06.2011, p. 449-453.

    Research output: Contribution to journalArticle

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