• DocumentCode
    3210383
  • Title

    The Study Based on Cluster Analysis of Investment Value of Listed Companies in Growth Enterprise Board

  • Author

    Yu, Gu ; Zhiqiang, He

  • Author_Institution
    Beijing Wuzi Univ., Beijing, China
  • Volume
    3
  • fYear
    2010
  • fDate
    11-12 May 2010
  • Firstpage
    970
  • Lastpage
    976
  • Abstract
    As an emerging board of capital market, GEB has two important features of high-growth and high-risk levels. To fully grasp the fundamentals of listed companies have great significance for investors. In this paper, which based on the financial data which had published on September 30, 2009 of the initial 28 GEB listed companies, the penman used cluster analysis and other data mining techniques to implement an empirical study on the fundamentals of listed companies, such as profitability capacities, solvency capacities, growth capacities, expansion capabilities, operational capabilities, the level of risk and so on. With the above study, the investors can not only easily set up the investment philosophy with fundamental analysis as the main and technical analysis as the second, but also rashly find out the stocks which have real investment value for long-term investment.
  • Keywords
    data mining; investment; pattern clustering; stock markets; capital market; cluster analysis; data mining techniques; expansion capabilities; growth capacities; growth enterprise board; investment value; listed companies; operational capabilities; profitability capacities; risk level; solvency capacities; Automation; Companies; Data analysis; Data mining; Helium; Information analysis; Investments; Profitability; Risk analysis; Stock markets; Cluster Analysis; Growth Enterprise Board (GEB); Investment Value;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on
  • Conference_Location
    Changsha
  • Print_ISBN
    978-1-4244-7279-6
  • Electronic_ISBN
    978-1-4244-7280-2
  • Type

    conf

  • DOI
    10.1109/ICICTA.2010.494
  • Filename
    5523598