A0370
Title: Local information advantage and stock returns: Evidence from social media
Authors: Feng Li - Peking University (China) [presenting]
Abstract: The information asymmetry between local and nonlocal investors with a large dataset of stock message board postings is examined. The abnormal relative postings of a firm, i.e., unusual changes in the volume of postings from local versus nonlocal investors, are documented to 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. The information driving return predictability through content-based analysis is identified. Abnormal relative postings also lead to analysts' forecast revisions. Overall, investors' interactions on social media contain valuable geography-based private information.
