Building a Rough Sets-Based Prediction Model of Tick-Wise Stock Price Fluctuations

Yoshiyuki Matsumoto*, Junzo Watada

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingChapter


    Rough sets enable us to mine knowledge in the form of IF-THEN decision rules from a data repository, a database, a web base, and others. Decision rules are used to reason, estimate, evaluate, and forecast. The objective of this paper is to build the rough sets-based model for analysis of time series data with tick-wise price fluctuations where knowledge granules are mined from the data set of tickwise price fluctuations. We show how a method based on rough sets helps acquire the knowledge from time-series data. The method enables us to obtain IF-THEN type rules for forecasting stock prices.

    Original languageEnglish
    Title of host publicationIntelligent Systems Reference Library
    Number of pages29
    Publication statusPublished - 2013

    Publication series

    NameIntelligent Systems Reference Library
    ISSN (Print)18684394
    ISSN (Electronic)18684408

    ASJC Scopus subject areas

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


    Dive into the research topics of 'Building a Rough Sets-Based Prediction Model of Tick-Wise Stock Price Fluctuations'. Together they form a unique fingerprint.

    Cite this