Identifying Information in Stock Message Boards and Its Implications for Stock Market Efficiency

The information value of stock message boards has often been debated. A main difficulty in assessing the value is the presence of a large number of posts with varying quality. This paper presents an intuitive approach to identify and aggregate information in stock message boards. We weigh each post’s recommendation by its author’s credibility based on accuracy of his past posts. We find that the weighted average recommendation of a stock message board has prediction power over future excessive returns of the stock. The effect is both statistically and economically significant. Interestingly, a simple average recommendation of a stock message board has no prediction power for future stock movements. These results indicate that there exist informed investors in stock message boards, but their information is neither fully incorporated into the market price, nor fully acknowledged by peers in stock message boards. An implementable trading strategy is developed to explore the information value of stock message boards. We find that significant economic gain can be achieved even after taking into consideration of trading costs. We also discuss various approaches to improve the information aggregation process and thus the performance of the trading strategy.