PDD Stock Price Prediction Using ARIMA Model

DOI

10.2991/978-94-6463-058-9_15How to use a DOI?

Keywords

Pingduoduo; stock price; time series; ARIMA model; adf test

Abstract

In order to study and predict the short-term stock price of pinduoduo, an emerging e-commerce company in China, the sample data of its closing prices of January 1, 2020, to January 1, 2021, are selected as the research object. Firstly, ADF stationarity test is used to judge whether the time series is stable, and then ARIMA model is established by R language. Based on the model, the prediction results of the last 13 data are tested. The results show that the ARIMA model can accurately predict pinduoduo's short-term stock price.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Yutong Ge
PY  - 2022
DA  - 2022/12/27
TI  - PDD Stock Price Prediction Using ARIMA Model
BT  - Proceedings of the 2nd International Conference on Internet, Education and Information Technology (IEIT 2022)
PB  - Atlantis Press
SP  - 83
EP  - 87
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-058-9_15
DO  - 10.2991/978-94-6463-058-9_15
ID  - Ge2022
ER  -