In this paper, according to the time series characteristics of financial data, such as stock index, stock price, etc, we introduce the Artificial Neural Network (ANN) and Recurrent Neural Network (RNN) in deep learning to stock index prediction and build a BP-LSTM model based on the Back Propagation (BP) neural network model and Long Short-Term Memory (LSTM) neural network model. Numerical analysis shows that the accuracy of our model is higher than that of the traditional machine learning models, and it also has some improvement compared with the ordinary LSTM model.
引用本文格式： 孙存浩,胡兵,邹雨轩. 指数趋势预测的BP-LSTM模型[J]. 四川大学学报: 自然科学版, 2020, 57: 27.复制