TITLE:
Stock Market Prediction Using Heat of Related Keywords on Micro Blog
AUTHORS:
Shengchen Zhou, Xunzhi Shi, Yunchen Sun, Wenting Qu, Yingzi Shi
KEYWORDS:
Micro Blog; Stock Market Prediction; Emotion; SVM
JOURNAL NAME:
Journal of Software Engineering and Applications,
Vol.6 No.3B,
April
10,
2013
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.