Exploring the attention mechanism in LSTM-based Hong Kong stock price movement prediction
Citations
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Cited by:
- Ewald, Christian Oliver & Li, Yaoyu, 2024. "The role of news sentiment in salmon price prediction using deep learning," Journal of Commodity Markets, Elsevier, vol. 36(C).
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- Niu, Hongli & Xu, Kunliang & Liu, Cheng, 2021. "A decomposition-ensemble model with regrouping method and attention-based gated recurrent unit network for energy price prediction," Energy, Elsevier, vol. 231(C).
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- Jiawei Wang & Zhen Chen, 2024. "Factor-GAN: Enhancing stock price prediction and factor investment with Generative Adversarial Networks," PLOS ONE, Public Library of Science, vol. 19(6), pages 1-26, June.
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- Hakan Gunduz, 2021. "An efficient stock market prediction model using hybrid feature reduction method based on variational autoencoders and recursive feature elimination," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-24, December.
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- Md Talha Mohsin & Nabid Bin Nasim, 2025. "Explaining the Unexplainable: A Systematic Review of Explainable AI in Finance," Papers 2503.05966, arXiv.org, revised Nov 2025.
- Minami, Koutaroh, 2025. "Detecting bubbles via deterioration in machine learning predictive accuracy," Finance Research Letters, Elsevier, vol. 86(PB).
- Hongli Niu & Qiaoying Pan & Kunliang Xu, 2023. "Hybrid deep learning models with multi-classification investor sentiment to forecast the prices of China’s leading stocks," PLOS ONE, Public Library of Science, vol. 18(11), pages 1-24, November.
- Yi Fu & Shuai Cao & Tao Pang, 2020. "A Sustainable Quantitative Stock Selection Strategy Based on Dynamic Factor Adjustment," Sustainability, MDPI, vol. 12(10), pages 1-12, May.
- Przemysław Grądzki & Piotr Wójcik & Stefan Lessmann, 2025. "Algorithmic crypto trading using information-driven bars, triple barrier labeling and deep learning," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-43, December.
- Grilli, Luca & Santoro, Domenico, 2020. "How Boltzmann Entropy Improves Prediction with LSTM," MPRA Paper 100578, University Library of Munich, Germany.
- Zhang, Yongjie & Chu, Gang & Shen, Dehua, 2021. "The role of investor attention in predicting stock prices: The long short-term memory networks perspective," Finance Research Letters, Elsevier, vol. 38(C).
- Qinkai Chen, 2021. "Stock Movement Prediction with Financial News using Contextualized Embedding from BERT," Papers 2107.08721, arXiv.org.
- Cheng Zhao & Ping Hu & Xiaohui Liu & Xuefeng Lan & Haiming Zhang, 2023. "Stock Market Analysis Using Time Series Relational Models for Stock Price Prediction," Mathematics, MDPI, vol. 11(5), pages 1-13, February.
- Chuting Sun & Qi Wu & Xing Yan, 2023. "Dynamic CVaR Portfolio Construction with Attention-Powered Generative Factor Learning," Papers 2301.07318, arXiv.org, revised Jan 2024.
- Yan Guo & Dezhao Tang & Wei Tang & Senqi Yang & Qichao Tang & Yang Feng & Fang Zhang, 2022. "Agricultural Price Prediction Based on Combined Forecasting Model under Spatial-Temporal Influencing Factors," Sustainability, MDPI, vol. 14(17), pages 1-18, August.
- Sun, Chuting & Wu, Qi & Yan, Xing, 2024. "Dynamic CVaR portfolio construction with attention-powered generative factor learning," Journal of Economic Dynamics and Control, Elsevier, vol. 160(C).
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- Wang, Chen & Shen, Dehua & Li, Youwei, 2022. "Aggregate Investor Attention and Bitcoin Return: The Long Short-term Memory Networks Perspective," Finance Research Letters, Elsevier, vol. 49(C).
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