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.
Highlights
Financial firms and academic researchers have recently begun to study the predictive value of information gathered from social media [1,2,3]
Perhaps more can be done by exploiting the sentiment in the content of the Twitter messages, combined with more sophisticated algorithmic models. This is an opportunity for future research. It is extremely difficult for individual investors to capitalize on newly released public information by trading in the stock markets
The speed of information exchange, ever-faster financial trading networks, and liquidity of financial markets, all ensure that market prices almost instantly absorb news as it is released to the public, denying arbitrage opportunities to all but exclusive groups of institutional traders [14]
Summary
Financial firms and academic researchers have recently begun to study the predictive value of information gathered from social media [1,2,3]. Researchers have begun to study the relationship between patterns observed on Twitter and stock market activity at daily levels of aggregation, we do not yet have much understanding of intra-day responses of the stock market in relation to the spread of news on Twitter. Such effects may be transitory and dissipate within hours or minutes, and it is precisely these effects that many algorithmic traders would like to exploit in real time.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
