IT DEPENDS ON WHEN YOU SEARCH

• 成果类型: Article
• 署名作者: Li, Jun; Liu, Xianwei; Ye, Qiang; Zhao, Feng; Zhao, Xiaofei
• 署名单位: University of Texas System; University of Texas Dallas; Harbin Institute of Technology; Chinese Academy of Sciences; University of Science & Technology of China, CAS; Georgetown University
• 刊物名称: MIS QUARTERLY
• ISSN/ISSBN: 0276-7783
• DOI: 10.25300/MISQ/2022/17234
• 发表日期: 2023
• 页码: 263-280
• 关键词: INVESTOR ATTENTION; information-technology; stock returns; cross-section; Social media; DUMB MONEY; MARKET; underreaction; Sentiment; IMPACT

摘要

Existing studies have found that online search is a revealed measure for investor attention and a useful predictor of stock returns. We study the heterogeneity in retail investor attention by comparing search conducted on weekdays vs. weekends and investigate the price pressure channel and information processing channel for stock return predictability. According to the information processing channel, weekends afford retail investors more time for the intensive cognitive analysis necessary to make better predictions. Alternatively, weekend search might better capture the price pressure from retail investors' trading activities. We provide empirical results that support the information processing channel. We first show that weekend search, rather than weekday search, predicts large-cap stock returns in both the cross-section and time series. Additionally, our findings on retail trading activity contradict the price pressure channel in that weekday search, rather than weekend search, leads to a subsequent retail order imbalance. Overall, our study contributes to the literature on the predictive power of online search on stock returns, which has mainly focused on the price pressure channel, which yields significant results for small-cap stocks only.