This paper aims to enhance the predictability of stock returns. Existing studies have used investor sentiment to forecast stock returns. However, it is unclear whether high-frequency intraday investor sentiment can enhance the forecasting performance of low-frequency stock returns.
Thus, we employ the MIDAS model and the high-frequency intraday sentiment extracted from the Internet stock forum to forecast Chinese A-shares returns at daily frequency.
The results illustrate that high-frequency sentiment data are better than daily sentiment data in predicting daily stock returns, and the sentiment in non-trading hours has been proved superior to those in trading hours.
First, our study adds to the growing literature on investor sentiment. We are the first to construct a proxy for high-frequency investor sentiment using intraday postings collected from Chinese Internet stock forum. Second, we confirm that sentiment in non-trading hours has a stronger predictive ability than those in trading hours. Third, we also contribute to the performance comparison of MIDAS-class models. The good performance of U-MIDAS is confirmed in our empirical applications.
