  In this paper, we propose a model to analyze sentiment of online stock forum
and use the information to predict the stock volatility in the Chinese market.
We have labeled the sentiment of the online financial posts and make the
dataset public available for research. By generating a sentimental dictionary
based on financial terms, we develop a model to compute the sentimental score
of each online post related to a particular stock. Such sentimental information
is represented by two sentiment indicators, which are fused to market data for
stock volatility prediction by using the Recurrent Neural Networks (RNNs).
Empirical study shows that, comparing to using RNN only, the model performs
significantly better with sentimental indicators.
