• DocumentCode
    2501068
  • Title

    Integration of artificial neural networks and fuzzy Delphi for stock market forecasting

  • Author

    Kuo, R.J. ; Lee, L.C. ; Lee, C.F.

  • Author_Institution
    Dept. of Marketing & Distribution Manage., Nat. Inst. of Technol., Kaohsiung, Taiwan
  • Volume
    2
  • fYear
    1996
  • fDate
    14-17 Oct 1996
  • Firstpage
    1073
  • Abstract
    The stock market, which has been investigated by various researchers, is a very complicated environment. So far, most of the research only concerned the quantitative factors, like index in open or volume, instead of qualitative factors, say political effect. However, the latter always plays a very important role in the stock market environment. Therefore, this research proposes an intelligent stock market forecasting system which considers the quantitative factors as well as the qualitative factors. Basically, the proposed system consists of (1) factors collection, (2) quantitative model (i.e., artificial neural network), (3) qualitative model (i.e., fuzzy Delphi), and (4) decision integration (i.e., artificial neural network). An example based on the Taiwan stock market is shown to evaluate the proposed intelligent system
  • Keywords
    forecasting theory; fuzzy set theory; knowledge based systems; neural nets; stock markets; Taiwan stock market; artificial neural networks; decision integration; factors collection; fuzzy Delphi method; intelligent stock market forecasting system; qualitative factors; quantitative model; Artificial intelligence; Artificial neural networks; Economic forecasting; Environmental management; Financial management; Fuzzy neural networks; Predictive models; Stock markets; Technology forecasting; Technology management;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics, 1996., IEEE International Conference on
  • Conference_Location
    Beijing
  • ISSN
    1062-922X
  • Print_ISBN
    0-7803-3280-6
  • Type

    conf

  • DOI
    10.1109/ICSMC.1996.571232
  • Filename
    571232