Mining opinion and sentiment for stock return prediction based on Web-forum messages

Abstract

Stock return prediction has drawn extensive attention in recent years. All kinds of time series-based methods are commonly utilized to predict future stock returns based on the statistical properties in the series. As more and more people gather in Web-based forums, sentiment and opinion in forums are likely turned into new indices for the movement of stock returns. We propose a novel method to forecast stock returns by mining opinion and sentiment from Web forum messages. Opinion about the drop and rise of stock prices is firstly extracted from the messages posted by forum users. Then unhealthy sentiment is recognized by means of pattern matching. A Bayesian model that incorporates opinion and unhealthy sentiment is established to infer the relation between stock returns and the combination of opinion and sentiment. Compared experiments on China A-share stock market and Guba Web forum are done, and the results show that the proposed method is effective.