• DocumentCode
    3529476
  • Title

    Prediction of financial time series based on information granulation

  • Author

    Xue, Mu-sen ; Gao, Hong

  • Author_Institution
    Coll. of Manage. & Econ., Tianjin Univ., Tianjin, China
  • Volume
    Part 3
  • fYear
    2011
  • fDate
    3-5 Sept. 2011
  • Firstpage
    1725
  • Lastpage
    1727
  • Abstract
    The prediction of financial time series produced by the stock market has been the research focus of scholars. However, we can not accurately predict the fluctuations in the future in most cases. In this paper, we try to apply information granulation in the prediction of financial time series. First, we fuzzy grain the financial time series. Then, we use RBF neural network which has good ability of nonlinear mapping to predict future trend of fluctuations and fluctuating range. Simulation result shows that this method can accurately predict the trend of fluctuations and the fluctuating range, which can provide reliable reference for the decision makers of investment.
  • Keywords
    fuzzy set theory; granular computing; prediction theory; radial basis function networks; stock markets; time series; RBF neural network; financial time series prediction; fluctuating range; fluctuation trend; fuzzy grain; granular computing; information granulation; nonlinear mapping; stock market; words calculation; Fitting; Fluctuations; Forecasting; Simulation; Stock markets; Time series analysis; RBF neural network; information granulation; prediction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Engineering and Engineering Management (IE&EM), 2011 IEEE 18Th International Conference on
  • Conference_Location
    Changchun
  • Print_ISBN
    978-1-61284-446-6
  • Type

    conf

  • DOI
    10.1109/ICIEEM.2011.6035497
  • Filename
    6035497