Proceedings of the 2025 3rd International Academic Conference on Management Innovation and Economic Development (MIED 2025)

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Predicting Apple’s Stock Price with LSTM

Authors
Yizheng Wang1, *, Zeyue Ge2, Tianzong Jian3, Haocheng Zhang3
1Department of Finance, Beijing University of Technology, Beijing, China
2Business School, Tianjin University of Finance and Economics, Tianjin, China
3Department of Westa College, Southwest University, Chongqing, China
*Corresponding author. Email: 2188662133@qq.com
Corresponding Author
Yizheng Wang
Available Online 17 September 2025.
DOI
10.2991/978-94-6463-835-6_102How to use a DOI?
Keywords
Long- and Short-Term Memory; Apple; Machine Learning; Deep Learning; Price Prediction
Abstract

In the capital market, accurate forecasting of stock prices is important for investors’ investment decisions as well as risk management. As the technology company with the highest market capitalization in the world, the movement of Apple’s stock price is highly concerned. However, traditional forecasting methods are often difficult to apply to the current increasingly complex capital market, thus making it difficult to capture the complex dynamics of stock price changes. In this study, a time-series analysis is performed on a dataset containing Apple’s stock price for the past eleven years to capture its long-term dependence by introducing a long-short-term memory model (LSTM). After experimental verification, the model performs well in terms of the Mean Squared Error and other indicators, and can reflect Apple’s stock price trend more accurately, which provides investors with a forecasting basis with practical reference value, and also provides a new modeling perspective and methodology for stock market time series forecasting research.

Copyright
© 2025 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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Volume Title
Proceedings of the 2025 3rd International Academic Conference on Management Innovation and Economic Development (MIED 2025)
Series
Advances in Economics, Business and Management Research
Publication Date
17 September 2025
ISBN
978-94-6463-835-6
ISSN
2352-5428
DOI
10.2991/978-94-6463-835-6_102How to use a DOI?
Copyright
© 2025 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.

Cite this article

risenwbib
TY  - CONF
AU  - Yizheng Wang
AU  - Zeyue Ge
AU  - Tianzong Jian
AU  - Haocheng Zhang
PY  - 2025
DA  - 2025/09/17
TI  - Predicting Apple’s Stock Price with LSTM
BT  - Proceedings of the 2025 3rd International Academic Conference on Management Innovation and Economic Development (MIED 2025)
PB  - Atlantis Press
SP  - 954
EP  - 960
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-835-6_102
DO  - 10.2991/978-94-6463-835-6_102
ID  - Wang2025
ER  -