All posts tagged with "Behavioral Finance" in reverse chronological order.
The purpose of this paper is to identify key channels through which gender is applied to financial research.
Using a unique sample of Twitter posts, also called tweets, we examine the impact of social media on the return, volume, and volatility of the stock market using word list and algorithmic content analysis. We show market returns may be predicted using confidence and sentiment levels. Volume is best predicted by confidence. Volatility is most related to sentiment. We examine one dimension of Twitter user characteristics, namely gender. Our results show that men are more confident and less optimistic than women when they communicate about stocks. We find differences in the ability of communications by men and women to predict market returns, volume, and volatility.
