Stock Price Prediction Based on LSTM Model

DOI

10.2991/978-94-6463-706-9_68How to use a DOI?

Keywords

LSTM model; Deep learning; Stock price prediction

Abstract

Deep learning techniques have increasingly been applied to stock price prediction. The LSTM model performs better in predicting time series data. In our paper, the LSTM model is used to predict the closing price trend of CSI 300 index, and we finally find that the constructed model has better prediction ability, which indicates that the deep learning model has better generalization ability and higher prediction accuracy, and provides theoretical and practical experience for broadening the application field of the deep learning technology, and further applying it in the field of quantitative investment.

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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TY  - CONF
AU  - Zihan Gao
PY  - 2025
DA  - 2025/05/07
TI  - Stock Price Prediction Based on LSTM Model
BT  - Proceedings of the 2024 2th International Conference on Economic Management, Financial Innovation and Public Service (EMFIPS 2024)
PB  - Atlantis Press
SP  - 762
EP  - 774
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-706-9_68
DO  - 10.2991/978-94-6463-706-9_68
ID  - Gao2025
ER  -