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Stock Market Prediction Using Heat of Related Keywords on Micro Blog

机译:利用微博客上相关关键词的热度进行股市预测

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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.
机译:股市投资者的情绪是否会影响股市本身,是金融研究的热点之一。本文提出了一种基于微博客相关关键词的发热量的方法,因为微博客是获取针对某一主题的公众意见的理想来源。我们选择上证综指作为研究对象,通过相关分析,格兰杰因果分析和支持向量机分类,结果表明,微博客上的关键词热度可以对股市进行短期预测,表达负面情绪具有更强大的预测能力。

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