TY - UNPB
T1 - News Diffusion in Social Networks and Stock Market Reactions
AU - Hirshleifer, David
AU - Peng, Lin
AU - Wang, Qiguang
PY - 2023/4
Y1 - 2023/4
N2 - We study how the social transmission of public news influences investors’ beliefs and securities markets. Using data on investor social networks, we find that earnings announcements from firms in higher-centrality locations generate 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. This evidence suggests that greater social connectedness promotes timely incorporation of news into prices, but also opinion divergence and excessive trading. We propose the social churning hypothesis and present supporting evidence with granular data from StockTwits messages and household trading records.
AB - We study how the social transmission of public news influences investors’ beliefs and securities markets. Using data on investor social networks, we find that earnings announcements from firms in higher-centrality locations generate 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. This evidence suggests that greater social connectedness promotes timely incorporation of news into prices, but also opinion divergence and excessive trading. We propose the social churning hypothesis and present supporting evidence with granular data from StockTwits messages and household trading records.
UR - https://www.nber.org/papers/w30860
U2 - 10.3386/w30860
DO - 10.3386/w30860
M3 - Working paper
T3 - NBER Working Paper Series
BT - News Diffusion in Social Networks and Stock Market Reactions
PB - National Bureau of Economic Research
ER -