Title

Stock Price Forecast Based on ARIMA Model and BP Neural Network Model

Authors

Jiaqi Qin, Wenzhou-Kean University
Zheng Tao, Wenzhou-Kean University
Shansong Huang, Wenzhou-Kean University
Gaurav Gupta, Wenzhou-Kean University

Document Type

Conference Proceeding

Publication Date

3-26-2021

Abstract

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.

Publication Title

2021 IEEE 2nd International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering, ICBAIE 2021

First Page Number

426

Last Page Number

430

DOI

10.1109/ICBAIE52039.2021.9389917

Recommended Citation

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.
https://digitalcommons.kean.edu/keanpublications/994