We examine how social networks shaped by high-speed rail connections influence investor attention and market reactions to earnings announcements in China. Firms in high-centrality cities exhibit stronger immediate and subsequent responses in investor attention, stock price, and trading volume to earnings news. Further analysis shows that earnings-induced local attention predicts future attention spillovers to intercity investors, amplifying both price and volume reactions after announcements. Overall, these findings indicate that high-speed rail networks foster investor social networks that facilitate the dissemination of firm news and help explain predictable patterns in investor behavior and market pricing.

We examine how pre-announcement weather conditions near a firm’s major institutional in- vestors affect stock market reactions to firms’ earnings announcements. We find that unpleasant weather experienced by institutional investors leads to more delayed market responses to sub- sequent earnings news. Moreover, unpleasant weather of institutional investors is associated with higher earnings announcement premia. The influence of institutional investors’ weather is robust after controlling for New York City weather, extreme weather conditions, and firm local weather. Additional cross-sectional evidence suggests that the strength of this weather effect is related to institutional investors’ trading behavior.

Based on a unique arrangement of trading and disclosure times around earnings announcements in the Chinese stock market, we provide evidence of a striking overnight-intraday disparity in terms of the reaction to earnings news. Specifically, we find that the overnight period exhibits a strong and consistent reaction to earnings announcements, whereas the intraday period trades against both the earnings news and the prior market reaction during the overnight period. In addition, we show that abnormal overnight returns on earnings announcement days exhibit strong predictability for future stock returns, consistent with the overnight returns containing valuerelevant signals. In contrast, we observe no return predictability for abnormal intraday returns on earnings announcement days, which as a result, also undermines the return predictability of abnormal daily returns. We propose possible explanations for the overnight-intraday disparity. We conclude that the differences in trading mechanisms between the two periods as well as in investor composition likely drive the phenomenon.