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Multi-sequential Neural Network Models for Stock Price Forecasting

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Proposing MSLSTM and MSLSTMA models improves stock price predictions in various industries, indicating potential for better investment strategies.

MSLSTMA achieved a winning rate of 95.83% in the telecommunication sector, outperforming traditional models.
Performance was evaluated using metrics like mean squared error and root mean squared error, showcasing MSLSTMA's superiority.
Both hybrid architectures effectively utilized LSTM to capture complex temporal dependencies in financial data.
Investors may benefit from improved stock price predictions, enhancing decision-making in various sectors.

Thomas et al. (2025) studied this question.

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Proposing MSLSTM and MSLSTMA models improves stock price predictions in various industries, indicating potential for better investment strategies.