Abstract
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.
Published Version
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