Using Convolutional Neural Network on Technical Analysis Indicators

• Main Authors: Jhao-Yu Liou, 劉昭雨
• Other Authors: Shi-Jim Yen
• Format: Others
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/32289485607677466547

碩士 === 國立東華大學 === 資訊工程學系 === 105 === Deep learning is a state of the art artificial intelligence technology, and the convolutional neural networks have been widely used in image recognition competitions. In the financial stock market, we often use the linear graph of various technical indexes to predict the trend. This paper uses the convolution neural network's excellent image recognition ability, combining the linear graph of various technical indicators, to predict the stock price as a classification problem, and to predict the results. The single stock's history data is too small. This paper uses the same kind of stocks as the single stock use, and collects the same kind of stock data into a linear graph of each technical index as input. Then trains the convolutional neural network, the results will be divided into two types of rising and. We also design a profit strategy base on the convolutional neural network.