Local Information Advantage and Stock Returns: Evidence from Social Media

We examine the information asymmetry between local and nonlocal investors with a large dataset of stock message board postings. We document that abnormal relative postings of a firm, i.e., unusual changes in the volume of postings from local versus nonlocal investors, capture locals' information advantage. This measure positively predicts firms' short-term stock returns as well as those of peer firms in the same city. Sentiment analysis shows that posting activities primarily reflect good news, potentially due to social transmission bias and short-sales constraints. We identify the information driving return predictability through content-based analysis. Abnormal relative postings also lead analysts' forecast revisions. Overall, investors' interactions on social media contain valuable geography-based private information.

Keywords: Local Information Advantage, Social Media, Topical Analysis, Sentiment Analysis, Return Predictability

JEL Classification: D82, G12, G14

Suggested Citation: Suggested Citation

Huang, Yuqin and Li, Feng and Li, Tong and Lin, Tse-Chun, Local Information Advantage and Stock Returns: Evidence from Social Media (January 15, 2024). Contemporary Accounting Research, Forthcoming, Available at SSRN: https://ssrn.com/abstract=2501937 or http://dx.doi.org/10.2139/ssrn.2501937