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January 1, 2026International Journal of Industrial and Systems Engineering

Stock market forecasting using a lion-algorithm-optimised hybrid LSTM model

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Key Points

The study aims to improve stock market forecasting accuracy through a novel hybrid LSTM model optimized using a lion algorithm.
Developed a hybrid LSTM model incorporating optimization techniques.
Utilized historical stock market data for training and validation.
Evaluated model performance against traditional forecasting methods.
Achieved a significant increase in prediction accuracy compared to standard LSTM models.
Demonstrated a reduction in forecasting error by 25% (p<0.05).
Provided insights into better decision-making in stock trading.

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Implication

Demonstrates improved stock market forecasting using a hybrid LSTM model, suggesting enhanced predictive accuracy.

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Cite This Study

Mengxu Li (2026) studied this question.

synapsesocial.com/papers/69f44390967e944ac5566c88 https://doi.org/10.1504/ijise.2026.10077996

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