Measurement of Individual Investor Sentiment and Its Application: Evidence from Chinese Stock Message Board

This paper investigates individual investor sentiment in Chinese stock message board Guba Eastmoney and its relation to the market returns and volatility. Focusing on measuring the sentiment, we propose a novel algorithm Semantic Orientation from Laplace Smoothed Normalized Pointwise Mutual Information(SO-LNPMI). We show that: (i) comparing to traditional methods, SO-LNPMI has higher accuracy and better adaptive property of probability estimate; (ii) negative sentiment is negatively correlated with market returns, whereas positive sentiment does not have any statistically significant impact on market returns; (iii) positive(negative) sentiment is negatively(positively) correlated with market volatility. Our results survive a range of robustness tests.

Automated summary

This paper investigates the relationship between individual investor sentiment in Chinese stock message board Guba Eastmoney and market returns and volatility. The authors propose a novel sentiment measurement algorithm called SO-LNPMI and demonstrate that it has higher accuracy and better adaptive property compared to traditional methods. The study finds that negative sentiment is negatively correlated with market returns, while positive sentiment does not have a statistically significant impact on market returns. Additionally, positive (negative) sentiment is negatively (positively) correlated with market volatility. These findings are robust across various tests.