Predicting Big Movers Based on Online Stock Forum Sentiment Analysis

نویسندگان

  • Mohammad Al-Ramahi
  • Yenling Chang
  • Omar F. El-Gayar
  • Jun Liu
چکیده

While social media sentiment has been proved to have predictive value for stock indices, it is intriguing to investigate if it is useful for predicting price changes for individual stocks. We focus on a special kind of stocks, big movers, i.e., stocks that undergo a drastic one-day price change, and a special kind of social media, online stock discussion forums. Based on an empirical study, our research shows that discussions during the days lead up to the big one-day price change do contain sentiments that can be used to predict big movers. The findings of our research have theoretical implications for future research on social media sentiment and practical implications for developing stock investment strategies.

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تاریخ انتشار 2015