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

ABSTRACT

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.

Keywords:

• individual investor sentiment
• SO-LNPMI algorithm
• market returns
• market volatility

Acknowledgments

We would like to thank the anonymous referees and the editor for very helpful suggestions and comments which led to improvements of our original paper.

Data Availability Statement

The data and code that support the findings of this study are available from the corresponding author upon reasonable request https://github.com/VincentWen0320/content-analysis website.

Supplementary Material

Supplemental data for this article can be accessed on the publisher’s website.

Notes

1. http://guba.eastmoney.com website.

2. More details about methodologies and empirical results of content analysis can be found in supplementary document.

3. The correlation matrix of variables are reported in supplementary document.

Additional information

Funding

This research was partially supported by the National Natural Science Foundation of P. R. China under Grant Nos. 71471020 and 71850008, Hunan Provincial Natural Science Foundation under Grant No. 2019JJ50650 and Scientific Research Fund of Hunan Provincial Education Department under Grant No. 18C0221.