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摘要:
Stock market has always been an important research field of scholars in various industries,and short-term stock price forecasting is the focus of both finance and computer research.This paper applies the convolutional neural network(CNN)to short-term stock price movement forecasting by using daily stock news of a famous company called Guizhoumaotai in the Chinese wine industry.Two scenarios were taken into consideration:first,the news occurred in a day’s transaction time was used to predict the day’s stock price movement;second,the news occurred before a day’s opening time and after the transaction time of the previous day was used to predict the day’s stock price movement.In addition,the stock attentions of Baidu search index and/or media index were added into the model to explore whether they have significant improvement on prediction.The experimental results show that using the news data of the day can achieve better prediction performance.In addition,the introduction of Baidu Index improves the result of stock price prediction to some extent however,with a little effect.
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篇名 Study of CNN-Based News-Driven Stock Price Movement Prediction in the A-Share Market
来源期刊 国际计算机前沿大会会议论文集 学科 经济
关键词 Stock price Deep learning CNN Baidu index
年,卷(期) 2020,(2) 所属期刊栏目
研究方向 页码范围 467-474
页数 8页 分类号 F42
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国际计算机前沿大会会议论文集
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北京市海淀区西三旗昌临801号
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