We show that valuation uncertainty and information arrival are two key characteristics of factors that determine whether they are affected by sentiment or limited attention. Moreover, individual factors of the leading factor models do not have significant loadings on these two characteristics...

Using the minute-frequency data of the top 30 coins listed on Binance, which represent 86% of the total dollar trading volume of the cryptocurrency market, we document strong evidence of cross-cryptocurrency return predictability. The lagged returns of other cryptocurrencies serve as significant...

The 2017 bubble on the cryptocurrency market recalls our memory in the dot-com bubble, during which hard-to-measure fundamentals and investors' illusion for brand new technologies led to overvalued prices. Benefiting from the massive increase in the volume of messages published on social media...

We examine the effect of investor attention spillover on stock return predictability. Using a novel measure, the News Network Triggered Attention index (NNTA), we find that NNTA negatively predicts market returns with a monthly in(out)-of-sample R-square of 5.97% (5.80%). In the cross-section, a...

Using the minute-frequency data on Binance, we find strong evidence of cross-cryptocurrency return predictability. The lagged returns of other cryptocurrencies serve as significant predictors of focal cryptocurrencies up to ten minutes, in line with slow information diffusion. The results are...

Media news may cover multiple firms in one article, which establishes a media connection across firms. We propose a media connection strength (MCS) measure, which defined as the number of news articles co-mentioning two firms. We find that the MCS measure can capture soft information about the...

Trading outside the main session occurs between 4:00PM-8:00PM and 4:00AM-9:30AM and is typically dominated by institutional investors, as retail investors are discouraged to trade in the extended trading hours. This study examines whether trading in the extended hours is predictive of future...