• DocumentCode
    2579463
  • Title

    Is stock BBS content correlated with the stock market? — A Japanese case

  • Author

    Maruyama, Ken ; Suwa, Hirohiko ; Umehara, Eiichi ; Ohta, Toshizumi

  • Author_Institution
    Next Solutions Inc., Tokyo, Japan
  • fYear
    2009
  • fDate
    11-14 Oct. 2009
  • Firstpage
    4601
  • Lastpage
    4606
  • Abstract
    We analyze the relations between the stock market and a stock bulletin board system (BBS) in Japan. Previous studies in the USA found that the characteristics of messages posted on stock BBSs can predict market volatility and trading volume. We develop hypotheses based on the results of those analyses and apply statistical analysis to the data about companies mentioned in a large number of messages posted on the Yahoo! stock message board in Japan in 2005-2006. We analyze the contents of these messages using natural language processing. We find a significant correlation between the number of postings and market volatility and trading volume, and also find significant correlation between the amount of bullish and bearish opinion and the stock return.
  • Keywords
    learning (artificial intelligence); natural language processing; statistical analysis; stock markets; support vector machines; Japan; Yahoo! stock message board; machine learning; market volatility; natural language processing; statistical analysis; stock bulletin board system; stock market; stock return; support vector machine; trading volume; Cybernetics; Discussion forums; Economic forecasting; Information analysis; Information systems; Internet; Natural language processing; Statistical analysis; Stock markets; USA Councils; machine learning; natural language processing; stock BBS; stock market; support vector machine;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man and Cybernetics, 2009. SMC 2009. IEEE International Conference on
  • Conference_Location
    San Antonio, TX
  • ISSN
    1062-922X
  • Print_ISBN
    978-1-4244-2793-2
  • Electronic_ISBN
    1062-922X
  • Type

    conf

  • DOI
    10.1109/ICSMC.2009.5346768
  • Filename
    5346768