• DocumentCode
    3409485
  • Title

    Grey topological prediction method and implication in China´s stock market price index

  • Author

    Tao, Sun ; Weijia, Li

  • Author_Institution
    Nanjing Univ. of Aeronaut. & Astronaut., Nanjing, China
  • fYear
    2009
  • fDate
    10-12 Nov. 2009
  • Firstpage
    614
  • Lastpage
    618
  • Abstract
    Stock index in security market directly reflects the trend and level of the overall market stock price. Therefore, the price prediction directly affects investment decisions and is closely related to economic interest of investors. However, with specific volatility and uncertainty in stock market, changes in stock price index are influenced by many factors, which make it very difficult for the traditional forecasting methods to achieve effective results. The gray system theory founded in late 20th century has been applied to stock market forecast and has made some achievements. In order to explore the effective way of forecasting stock index in China´s stock market, this article adopts gray topological prediction method and builds a gray topological prediction model to predict the trend of stock index and the level according to China´s stock market index changes. Furthermore, we verify the model using the Shanghai Composite index (closing price) and obtain satisfactory results. By providing a large number of stock investors with an effective way to predict the stock price index, the model is meaningful to improve the investment efficiency and minimize investment risks.
  • Keywords
    grey systems; pricing; stock markets; grey topological prediction method; price prediction; stock market price index; Discrete transforms; Economic forecasting; Intelligent systems; Investments; Prediction methods; Predictive models; Security; Stock markets; Sun; Topology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Grey Systems and Intelligent Services, 2009. GSIS 2009. IEEE International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4244-4914-9
  • Electronic_ISBN
    978-1-4244-4916-3
  • Type

    conf

  • DOI
    10.1109/GSIS.2009.5408241
  • Filename
    5408241