Social Data Predictive Power Comparison Across Information Channels and User Groups: Evidence from the Bitcoin Market
AbstractIn 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.
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: 20 may 2019.