On exploring the impact of users’ bullish-bearish tendencies in online community on the stock market

摘要

The online financial community enables non-professional individual investors to express opinions, share information and even spread emotions through the Internet. This paper uses 5,178,824 comments published in an online financial community to study the users’ bullish-bearish tendencies on the stock market. To that end, we propose a convolutional neural network based classifier to extract users’ tendencies from their comments, and introduce the distributed lag model and the GARCH model to investigate the impact of users’ tendencies on market volatility and market returns. The results show that the online users’ bearish tendencies are reflected in stronger market volatility and higher market returns, and the consistency of online users’ tendencies has a positive impact on market volatility.