Application of Stock Analysis Using Deep Learning

Abstract

The stock market plays a very important role in the entire financial market, and one of the most attractive research issues in predicting stock price fluctuations. Since the trend of stocks is usually related to the previous stock price, this paper uses a neural network with memory capability: Recurrent neural network (RNN). In order to improve its performance, Long Short Term Memory (LSTM) architecture was used. LSTM improves the long-term dependence of traditional RNNs and effectively improves the accuracy and stability of stability.