Media-based investor sentiment and stock returns: a textual analysis based on newspapers

Abstract

This study constructs a media-based investor sentiment index based on a textual analysis of China’s leading financial newspapers. We employ both the Word2Vec technique and the dictionary method to measure the aggregate textual tone in the media news. Based on a sample of publicly listed A-share firms in China, we document that media-based sentiment is positively (negatively) related to the cross-section of stock returns over a short (long) horizon. Further analysis shows that higher information quality, measured by more analyst coverage, better audit opinions and non-governmental ownership could mitigate the effects of sentiment. Overall, our findings imply that media news contains important information for measuring the overall investor sentiment that drives the future stock price up in the short term and then down in the long term.