Abstract
In this paper, we examined the effects of financial news on Ho Chi Minh Stock Exchange (HoSE) and we tried to predict the direction of VN30 Index after the news articles were published. In order to do this study, we got news articles from three big financial websites and we represented them as feature vectors. Recently, researchers have used machine learning technique to integrate with financial news in their prediction model. Actually, news articles are important factor that influences investors in a quick way so it is worth considering the news impact on predicting the stock market trends. Previous works focused only on market news or on the analysis of the stock quotes in the past to predict the stock market behavior in the future. We aim to build a stock trend prediction model using both stock news and stock prices of VN30 index that will be applied in Vietnam stock market while there has been a little focus on using news articles to predict the stock direction. Experiment results show that our proposed method achieved high accuracy in VN30 index trend prediction.
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