• DocumentCode
    624633
  • Title

    A fundamental analysis-based method for stock market forecasting

  • Author

    Yuh-Jen Chen ; Yuh-Min Chen

  • Author_Institution
    Dept. of Accounting & Inf. Syst., Nat. Kaohsiung First Univ. of Sci. & Technol., Kaohsiung, Taiwan
  • fYear
    2013
  • fDate
    9-11 June 2013
  • Firstpage
    354
  • Lastpage
    359
  • Abstract
    By considering financial conditions of listed companies, industrial environment, macroeconomics, and financial news, this study developed a decision support system for a fundamental analysis-based stock market forecasting to select optimal stocks from the stock market and predict their future price trends to provide a reference for investor decisions. The tasks involved in the study include: (i) design a fundamental analysis-based approach to stock market forecasting, (ii) develop techniques related to fundamental analysis-based stock market forecasting, and (iii) demonstrate the proposed fundamental analysis-based approach to stock market forecasting. The fundamental analysis-based approach to stock market forecasting involves techniques such as calculating the weight of financial indicators, evaluating and selecting individual stocks, selecting financial news features, determining stock trading signals based on financial news, and forecasting stock price trend.
  • Keywords
    decision support systems; economic forecasting; macroeconomics; share prices; stock markets; decision support system; financial news; financial news features; fundamental analysis-based stock market forecasting; industrial environment; investor decisions; listed companies; macroeconomics; stock price trend; stock trading signals; Accuracy; Bayes methods; Forecasting; Market research; Stock markets; Testing; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Information Processing (ICICIP), 2013 Fourth International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4673-6248-1
  • Type

    conf

  • DOI
    10.1109/ICICIP.2013.6568097
  • Filename
    6568097