Stock Prediction Using Convolutional Neural Network

Stock prediction is a very hot topic in our life. However, in the early time, because of some reasons and the limitation of the device, only a few people had the access to the study. Thanks to the rapid development of science and technology, in recent years more and more people are devoted to the study of the prediction and it becomes easier and easier for us to make stock prediction by using different ways now, including machine learning, deep learning and so on. In this paper, we proposed a deep learning method based on Convolutional Neural Network to predict the stock price movement of Chinese stock market. We set the opening price, high price, low price, closing price and volume of stock deriving from the internet as input of the architecture and then run and test the program. The result has shown that it is a bit reliable to use deep learning method based on Convolutional Neural Network to predict the stockprice movement of China.

• Publication year

  2018

• Venue

  IOP Conference Series: Materials Science and Engineering

• Publication date

  2018-11-05

• Fields of study

  Physics, Business, Computer Science

• Identifiers
  DOI 10.1088/1757-899X/435/1/012026
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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