Stock Market Prediction Using Heat of Related Keywords on Micro Blog

Shengchen Zhou, Xunzhi Shi, Yunchen Sun, Wenting Qu, Yingzi Shi

Sydney Institute of Language & Commerce, Shanghai University, Shanghai, China.

DOI: 10.4236/jsea.2013.63B009                

Abstract

Whether the stock market investors’ emotion can influence the stock market itself is one of the hot topic in financial research. In this paper, a method based on the heat of related keywords on Micro Blog is proposed, as Micro Blog is an ideal source for capturing public opinions towards certain topic. We choose Shanghai Composite index as the research object, through correlation analysis, Granger causality analysis, and support vector machine classification, the results have shown that the keywords heat on micro blog can make a short-time prediction of stock market, and the keyword which expresses negative emotion have more powerful prediction ability.

Keywords

Micro Blog; Stock Market Prediction; Emotion; SVM

Conflicts of Interest

The authors declare no conflicts of interest.

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