Stock Trend Prediction of Communication Industry Based on LSTM Neural Network Algorithm and Research of Industry Development Strategy: – A Case Study of Zhongxing Telecommunication Equipment Corporation

Abstract

Based on the background of "ZTE event" in China-US trade friction, in order to effectively analyze the stock trend of communication industry in the securities market, this paper uses the long short-term memory (LSTM) neural network to establish a deep learning model, taking stock of Zhongxing Telecommunication Equipment Corporation as the specific research object, and predicts the stock price of ZTE within two years after the outbreak of "ZTE event" The prediction results are compared with the actual stock price and the experimental results show that the proposed method can effectively predict the development trend of the stock. Based on the research results, this paper analyzes the future development of China's communication industry under the background of China-US trade friction, and puts forward the corresponding industry development strategy, which provides reference for the development strategy of Chinese communication enterprises.