Stock Price Forecast Based on ARIMA Model and BP Neural Network Model
This paper uses the ARIMA model and BP neural network to model and predict the closing prices of the two stocks of JD and PDD from July 26, 2018 to January 29, 2021 (1266 data in total). First, use Python to visualize the time series of the two stock data. Then, establish ARIMA model and BP neural network. Meanwhile, the forecasting accuracy of the two models is compared, and the final result shows that both of the two prediction models can achieve relatively ideal forecasting accuracy.
2021 IEEE 2nd International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering, ICBAIE 2021
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Qin, Jiaqi; Tao, Zheng; Huang, Shansong; and Gupta, Gaurav, "Stock Price Forecast Based on ARIMA Model and BP Neural Network Model" (2021). Kean Publications. 994.