Real-Time Diffusion of Information on Twitter and the Financial Markets

Ali Tafti; Ryan Zotti; Wolfgang Jank

doi:10.1371/journal.pone.0159226

Real-Time Diffusion of Information on Twitter and the Financial Markets

PLoS One. 2016 Aug 9;11(8):e0159226. doi: 10.1371/journal.pone.0159226. eCollection 2016.

Authors

Ali Tafti¹, Ryan Zotti², Wolfgang Jank³

Affiliations

¹ Department of Information and Decision Sciences, College of Business Administration, University of Illinois at Chicago, Chicago, Illinois, United States of America.
² Capital One Corporation, Richmond, Virginia, United States of America.
³ Department of Information Systems Decision Sciences, Muma College of Business, University of South Florida, Tampa, Florida, United States of America.

Abstract

Do spikes in Twitter chatter about a firm precede unusual stock market trading activity for that firm? If so, Twitter activity may provide useful information about impending financial market activity in real-time. We study the real-time relationship between chatter on Twitter and the stock trading volume of 96 firms listed on the Nasdaq 100, during 193 days of trading in the period from May 21, 2012 to September 18, 2013. We identify observations featuring firm-specific spikes in Twitter activity, and randomly assign each observation to a ten-minute increment matching on the firm and a number of repeating time indicators. We examine the extent that unusual levels of chatter on Twitter about a firm portend an oncoming surge of trading of its stock within the hour, over and above what would normally be expected for the stock for that time of day and day of week. We also compare the findings from our explanatory model to the predictive power of Tweets. Although we find a compelling and potentially informative real-time relationship between Twitter activity and trading volume, our forecasting exercise highlights how difficult it can be to make use of this information for monetary gain.

MeSH terms

Diffusion
Financial Management / statistics & numerical data*
Humans
Models, Statistical
Social Media / statistics & numerical data*
Time Factors

Grants and funding

Besides financial support provided by our academic institutions, in the form of salaries, computing equipment, or university research grants, this research has not been funded by any other entity. One of the co-authors, RZ, now works at CapitalOne Corporation; his contributions to this paper, in the original design of research and development of the data collection software program, were made while he was a student at the University of Illinois at Urbana-Champaign. Subsequently, although CapitalOne provided support in the form of salary for RZ, the firm did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. In short, RZ’s current employer has no role or interest in this study. The specific roles of authors are articulated in the ‘author contributions’ section.