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Deep learning for Stock Market Prediction

Citations

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Cited by:

  1. Mohammed El Amine Senoussaoui & Mostefa Brahami & Issouf Fofana, 2021. "Transformer Oil Quality Assessment Using Random Forest with Feature Engineering," Energies, MDPI, vol. 14(7), pages 1-15, March.
  2. Damian Ślusarczyk & Robert Ślepaczuk, 2023. "Optimal Markowitz Portfolio Using Returns Forecasted with Time Series and Machine Learning Models," Working Papers 2023-17, Faculty of Economic Sciences, University of Warsaw.
  3. Zefan Dong & Yonghui Zhou, 2024. "A Novel Hybrid Model for Financial Forecasting Based on CEEMDAN-SE and ARIMA-CNN-LSTM," Mathematics, MDPI, vol. 12(16), pages 1-16, August.
  4. Namitha Yeldho & Dany Thomas & Vimal George Kurian & Chandralekha Arathy & Ajithakumari Vijayappan Nair Biju, 2025. "Are machine learning models effective in predicting emerging markets? Investigating the accuracy of predictions in emerging stock market indices," Quality & Quantity: International Journal of Methodology, Springer, vol. 59(1), pages 839-904, February.
  5. Mufhumudzi Muthivhi & Terence L. van Zyl, 2022. "Fusion of Sentiment and Asset Price Predictions for Portfolio Optimization," Papers 2203.05673, arXiv.org.
  6. B. Prakash & B. Saleena, 2025. "Stock Market Prediction Using Deep Attention Bi-directional Long Short-Term Memory," Computational Economics, Springer;Society for Computational Economics, vol. 66(1), pages 903-927, July.
  7. Ioan Mihail Savaniu & Alexandru-Polifron Chiriță & Oana Tonciu & Magdalena Culcea & Ancuta Neagu, 2023. "Neural-Network-Based Time Control for Microwave Oven Heating of Food Products Distributed by a Solar-Powered Vending Machine with Energy Management Considerations," Energies, MDPI, vol. 16(19), pages 1-22, October.
  8. Xiaolu Wei & Yubo Tian & Na Li & Huanxin Peng, 2024. "Evaluating ensemble learning techniques for stock index trend prediction: a case of China," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 23(3), pages 505-530, September.
  9. S. Divyashree & Christy Jackson Joshua & Abdul Quadir Md & Senthilkumar Mohan & A. Sheik Abdullah & Ummul Hanan Mohamad & Nisreen Innab & Ali Ahmadian, 2024. "Enabling business sustainability for stock market data using machine learning and deep learning approaches," Annals of Operations Research, Springer, vol. 342(1), pages 287-322, November.
  10. Pawan Kumar Singh & Anushka Chouhan & Rajiv Kumar Bhatt & Ravi Kiran & Ansari Saleh Ahmar, 2022. "Implementation of the SutteARIMA method to predict short-term cases of stock market and COVID-19 pandemic in USA," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(4), pages 2023-2033, August.
  11. Priyank Sonkiya & Vikas Bajpai & Anukriti Bansal, 2021. "Stock price prediction using BERT and GAN," Papers 2107.09055, arXiv.org.
  12. Tianyu Zhou & Pinqiao Wang & Yilin Wu & Hongyang Yang, 2024. "FinRobot: AI Agent for Equity Research and Valuation with Large Language Models," Papers 2411.08804, arXiv.org.
  13. Nabanita Das & Bikash Sadhukhan & Rajdeep Ghosh & Satyajit Chakrabarti, 2024. "Developing Hybrid Deep Learning Models for Stock Price Prediction Using Enhanced Twitter Sentiment Score and Technical Indicators," Computational Economics, Springer;Society for Computational Economics, vol. 64(6), pages 3407-3446, December.
  14. Juan C. King & Roberto Dale & Jos'e M. Amig'o, 2024. "Blockchain Metrics and Indicators in Cryptocurrency Trading," Papers 2403.00770, arXiv.org.
  15. Suya Jin & Guiyan Liu & Qifeng Bai, 2023. "Deep Learning in COVID-19 Diagnosis, Prognosis and Treatment Selection," Mathematics, MDPI, vol. 11(6), pages 1-16, March.
  16. King, Juan C. & Dale, Roberto & Amigó, José M., 2024. "Blockchain metrics and indicators in cryptocurrency trading," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
  17. Stanislav Selitskiy, 2025. ""It Looks All the Same to Me": Cross-index Training for Long-term Financial Series Prediction," Papers 2511.08658, arXiv.org.
  18. Yiyang Zheng, 2022. "Neural Network and Order Flow, Technical Analysis: Predicting short-term direction of futures contract," Papers 2203.12457, arXiv.org.
  19. Tidor-Vlad Pricope, 2021. "Deep Reinforcement Learning in Quantitative Algorithmic Trading: A Review," Papers 2106.00123, arXiv.org.
  20. Li-Chen Cheng & Yu-Hsiang Huang & Ming-Hua Hsieh & Mu-En Wu, 2021. "A Novel Trading Strategy Framework Based on Reinforcement Deep Learning for Financial Market Predictions," Mathematics, MDPI, vol. 9(23), pages 1-16, November.
  21. Pedro M. Mirete-Ferrer & Alberto Garcia-Garcia & Juan Samuel Baixauli-Soler & Maria A. Prats, 2022. "A Review on Machine Learning for Asset Management," Risks, MDPI, vol. 10(4), pages 1-46, April.
  22. Satya Verma & Satya Prakash Sahu & Tirath Prasad Sahu, 2024. "Two-Stage Hybrid Feature Selection Approach Using Levy’s Flight Based Chicken Swarm Optimization for Stock Market Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 63(6), pages 2193-2224, June.
  23. Tariq Mahmood & Ibtasam Ahmad & Malik Muhammad Zeeshan Ansar & Jumanah Ahmed Darwish & Rehan Ahmad Khan Sherwani, 2024. "Comparative Study of Long Short-Term Memory (LSTM) and Quantum Long Short-Term Memory (QLSTM): Prediction of Stock Market Movement," Papers 2409.08297, arXiv.org.
  24. Muhammad Safiullah, Madiha Sher,MuhammadKashan,Adeel Rehman, Yasir Saleem Afridi, 2024. "Stock Market Analysis and Prediction Using Deep Learning," International Journal of Innovations in Science & Technology, 50sea, vol. 6(5), pages 329-337, June.
  25. Arvind Kumar Sinha & Pradeep Shende, 2024. "Uncertainty Optimization Based Feature Selection Model for Stock Marketing," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 357-389, January.
  26. Kaike Sa Teles Rocha Alves & Rosangela Ballini & Eduardo Pestana de Aguiar, 2025. "Financial Series Forecasting: A New Fuzzy Inference System for Crisp Values and Interval-Valued Predictions," Computational Economics, Springer;Society for Computational Economics, vol. 65(6), pages 3673-3721, June.
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