Tweeting for Money: Social Media and Mutual Fund Flows

• Authors: Juan F. Imbet and Javier Gil-Bazo.
• BSE Working Paper: 110837 | October 22
• Keywords: mutual funds , machine learning , persuasion , social media , Twitter , mutual fund , flows , textual analysis
• JEL codes: G11, G23, D83
• mutual funds
• machine learning
• persuasion
• social media
• Twitter
• mutual fund
• flows
• textual analysis

We investigate whether asset management firms use social media to persuade investors. Combining a database of almost 1.6 million Twitter posts by U.S. mutual fund families with textual analysis, we find that flows of money to mutual funds respond positively to tweets with a positive tone. Consistently with the persuasion hypothesis, positive tweets work best when they convey advice or views on the market and when investor sentiment is higher. Using a high-frequency approach, we are able to identify a short-lived impact of families’ tweets on ETF share prices. Finally, we reject the alternative hypothesis that asset management companies use social media to alleviate information asymmetries by either lowering search costs or disclosing privately observed information.