中文摘要：

互联网金融信息对于金融市场的影响在当代已经越来越不可忽视。面对海量的信息，其中大部分为非结构化的文本数据，该论文结合目前已有的文本倾向性算法，把信息的褒贬值作为外部变量加入到针对股价波动率建立的时间序列模型中去，对金融市场的股价波动率进行预测。实验揭示出金融市场波动率与互联网上金融新闻的相关性，并且提出了一种有效的股市预测方法。

英文摘要：

The financial information on Internet is more and more important to the stock market. Facing the countless news-most of which are non-strutted text： we adopt the sentiment of the news as an extra fact into the modeling of the price volatility of the financial market. The result proves that the correlations between the information sentiment and the asset price volatility, suggesting a new way to predict the stock market efficiently.