Social Data Predictive Power Comparison Across Information Channels and User Groups: Evidence from the Bitcoin Market

  • Peng Xie
  • Jiming Wu
  • Chongqi Wu

Abstract

In  the  context  of  Bitcoin,  we  examine  the  relationship  between  Bitcoin  price movement  and  social  data  sentiment.  Baseline  findings  reveal  that  social  media provides value-relevant information in both short-term and long-term predictions. By  comparing the  predictive  power  across  different  information  channels  and different user groups, we found that (1) while speculative information predicts both long-term and short-term returns effectively, fundamental-related information only predicts long-term returns, and that (2) prediction accuracy is higher for less active users than for active users on social media, especially in long-term prediction.
Published
2017-07-01
How to Cite
XIE, Peng; WU, Jiming; WU, Chongqi. Social Data Predictive Power Comparison Across Information Channels and User Groups: Evidence from the Bitcoin Market. The Journal of Business Inquiry, [S.l.], v. 17, n. 1, p. 41-54, july 2017. ISSN 2155-4072. Available at: <http://journals.uvu.edu/index.php/jbi/article/view/65>. Date accessed: 14 nov. 2018.