A Volatility-Responsive LSTM Approach for Predicting KLCI Closing Prices Using Dynamic Optimizer Switching
In financial time series forecasting, the ability of models to adapt to changing market conditions is critical for improving prediction accuracy. This study explores a novel approach to optimizing Long Short-Term Memory (LSTM) models by dynamically adjusting optimizers based on market volatility, sp...
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| Main Authors: | , |
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| Format: | Article |
| Language: | en |
| Published: |
Penerbit UTM Press
2025
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/49461/1/Published%20Paper_Matematika%202.pdf http://ir.unimas.my/id/eprint/49461/ https://matematika.utm.my/index.php/matematika/article/view/1581 https://doi.org/10.11113/matematika.v41.n2.1581 |
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