News Diffusion in Social Networks and Stock Market Reactions
David Hirshleifer, Lin Peng, Qiguang Wang
Abstract
Abstract We study how the social transmission of public news influences investors’ beliefs and the securities markets. Using data on social networks, we find that earnings announcements from firms in higher-centrality counties generate a stronger immediate price, volatility, and trading volume reactions. Post-announcement, such firms experience weaker price drift and faster volatility decay but higher and more persistent volume. These findings suggest greater social connectedness facilitates the timely incorporation of news into prices, as well as opinion divergence and excessive trading. We propose the social churning hypothesis, which is confirmed using granular data from StockTwits messages and household trading records.