• DocumentCode
    2604778
  • Title

    Research on predicting stock price by using fuzzy rough set

  • Author

    Xiao-feng, Hui ; Song-song, Li

  • Author_Institution
    Sch. of Manage., Harbin Inst. of Technol., Harbin, China
  • fYear
    2010
  • fDate
    24-26 Nov. 2010
  • Firstpage
    1124
  • Lastpage
    1130
  • Abstract
    With the aim of getting more accurate and more reliable stock price predicted results, this paper proposes an effective method which is fuzzy rough set and data mining technology. Firstly, stock prices were classified to some groups according to their different time attribute by using fuzzy set and rough set means. Then we calculated truth values of these groups respectively based on the given fuzzy relation, and derived some candidates of regulations by data mining method. In the end, we chose the useful regulations corresponding the time period and predicted the trend of stock price during the certain time period. This study shows that the method, which using fuzzy rough set and dada mining could make the predicted results is more effective.
  • Keywords
    data mining; fuzzy set theory; rough set theory; stock markets; data mining technology; fuzzy rough set; stock price prediction; Approximation methods; Biological system modeling; Data mining; Databases; Set theory; Stock markets; data mining; fuzzy rough set; stock price; truth value;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Management Science and Engineering (ICMSE), 2010 International Conference on
  • Conference_Location
    Melbourne, VIC
  • ISSN
    2155-1847
  • Print_ISBN
    978-1-4244-8116-3
  • Type

    conf

  • DOI
    10.1109/ICMSE.2010.5719937
  • Filename
    5719937