journal article·2025Open access

Research on Stock Price Prediction Method Based on the GAN-LSTM-Attention Model

Peng Li, Yanrui Wei, Lili Yin

Computers, Materials & Continua· Volume 82· Issue 1

Abstract

Stock price prediction is a typical complex time series prediction problem characterized by dynamics, nonlinearity, and complexity. This paper introduces a generative adversarial network model that incorporates an attention m... | Find, read and cite all the research you need on Tech Science Press
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Research context

OpenAlex topics: Grey System Theory Applications · Advanced Decision-Making Techniques

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References (24)

Show source-provided references
1. Fusion in stock market prediction: A decade survey on the necessity, recent developments, and potential future directions10.1016/j.inffus.2020.08.019 ↗
2. Stock return prediction with multiple measures using neural network models10.1186/s40854-023-00608-w ↗
3. Stock prediction based on technical indicators using deep learning model
4. A convolutional neural network based approach to financial time series prediction10.1007/s00521-022-07143-2 ↗
5. Machine learning techniques and data for stock market forecasting: A literature review
6. Stock market prediction with big data through hybridization of data mining and optimized neural network techniques
7. Extending machine learning prediction capabilities by explainable AI in financial time series prediction10.1016/j.asoc.2022.109876 ↗
8. Comparison of ARIMA and artificial neural networks models for stock price prediction10.1155/2014/614342 ↗
9. Prediction of BRIC stock price using ARIMA, SutteARIMA, and holt-winters
10. Stock return prediction under GARCH—An empirical assessment10.1016/j.ijforecast.2017.01.002 ↗
11. Quantifying StockTwits semantic terms’ trading behavior in financial markets: An effective application of decision tree algorithms10.1016/j.eswa.2015.08.008 ↗
12. Binary gravity search algorithm and support vector machine for forecasting and trading stock indices10.1016/j.iref.2022.11.009 ↗
13. An improved Stacking framework for stock index prediction by leveraging tree-based ensemble models and deep learning algorithms10.1016/j.physa.2019.122272 ↗
14. Deep neural networks, gradient-boosted trees, random forests: Statistical arbitrage on the S&P 50010.1016/j.ejor.2016.10.031 ↗
15. Research on stock trend prediction method based on optimized random forest10.1049/cit2.12067 ↗
16. Prediction model for stock price trend based on recurrent neural network10.1007/s12652-020-02057-0 ↗
17. LSTM based stock prediction using weighted and categorized financial news10.1371/journal.pone.0282234 ↗
18. A CNN-LSTM-based model to forecast stock prices
19. Forecasting stock prices using a hybrid deep learning model integrating attention mechanism, multi-layer perceptron, and bidirectional long-short term memory neural network10.1109/ACCESS.2020.3004284 ↗
20. Multi-model generative adversarial network hybrid prediction algorithm (MMGAN-HPA) for stock market prices prediction
21. A prediction model of stock market trading actions using generative adversarial network and piecewise linear representation approaches10.1007/s00500-022-07716-2 ↗
22. Stock market prediction with deep learning: The case of China10.1016/j.frl.2021.102209 ↗
23. Predicting LQ45 financial sector indices using RNN-LSTM
24. A novel ensemble learning approach for stock market prediction based on sentiment analysis and the sliding window method10.1109/TCSS.2022.3182375 ↗