High Frequency and Unstructured Data in Finance: An Exploratory Study of Twitter
|William Sanger1, Thierry Warin2*|
|*Corresponding Author: Thierry Warin, HEC Montreal, Department of International Business, 3000 Cote-Sainte-Catherine Road Montreal, Quebec, H3T 2A7, Canada|
Objective: In this paper, we investigate the question to know whether information spread over Twitter can be useful to design investment strategies on financial markets.
Methods: We compare the influence of two kinds of messages sent on Twitter over two types of returns concerning firms listed on the S&P500. We use logistic-based models to assess the probability of having certain types of returns based on messages published on Twitter.
Results: Financial tweets are positively correlated with higher intraday and overnight returns (1 to 5% returns) while being negatively correlated with lower returns (0 to 1% returns). Non-financial tweets are not significantly related to such returns.
Conclusion: From a practical standpoint, investment strategies could be designed following these findings to optimize some gain opportunities depending on the investment day, the targeted industry and live activity on Twitter.