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Forecasting the price of Bitcoin using deep learning

Citations

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Cited by:

  1. Yilun Zhang & Yuping Song & Ying Peng & Hanchao Wang, 2024. "Volatility forecasting incorporating intraday positive and negative jumps based on deep learning model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(7), pages 2749-2765, November.
  2. Ellwanger, Reinhard & Snudden, Stephen, 2025. "Putting VAR forecasts of the real price of crude oil to the test," Finance Research Letters, Elsevier, vol. 77(C).
  3. Si, Jingjian & Gao, Xiangyun & Zhou, Jinsheng, 2025. "Using deep learning to predict energy stock risk spillover based on co-investor attention," Finance Research Letters, Elsevier, vol. 74(C).
  4. Bouteska, Ahmed & Abedin, Mohammad Zoynul & Hajek, Petr & Yuan, Kunpeng, 2024. "Cryptocurrency price forecasting – A comparative analysis of ensemble learning and deep learning methods," International Review of Financial Analysis, Elsevier, vol. 92(C).
  5. Lu, Zhichao & Xu, Yuhong & Zhang, Yue & Zhao, Xinyao, 2025. "Is it difficult to predict the price movements of high-volatility assets," Finance Research Letters, Elsevier, vol. 85(PB).
  6. Lili Pan & Lin Wang & Qianqian Feng, 2022. "A Bibliometric Analysis of Risk Management in Foreign Direct Investment: Insights and Implications," Sustainability, MDPI, vol. 14(12), pages 1-18, June.
  7. Chenlu Dang & Fan Wang & Zimo Yang & Hongxia Zhang & Yufeng Qian, 2022. "RETRACTED ARTICLE: Evaluating and forecasting the risks of small to medium-sized enterprises in the supply chain finance market using blockchain technology and deep learning model," Operations Management Research, Springer, vol. 15(3), pages 662-675, December.
  8. Chengying He & Yong Li & Tianqi Wang & Salman Ali Shah, 2024. "Is cryptocurrency a hedging tool during economic policy uncertainty? An empirical investigation," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 11(1), pages 1-10, December.
  9. Kang, Mingu & Hong, Joongi & Kim, Suntae, 2025. "Harnessing technical indicators with deep learning based price forecasting for cryptocurrency trading," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 660(C).
  10. Samuka Mohanty & Rajashree Dash, 2022. "Neural Network-Based Bitcoin Pricing Using a New Mutated Climb Monkey Algorithm with TOPSIS Analysis for Sustainable Development," Mathematics, MDPI, vol. 10(22), pages 1-23, November.
  11. Cynthia Weiyi Cai & Rui Xue & Bi Zhou, 2023. "Cryptocurrency puzzles: a comprehensive review and re-introduction," Journal of Accounting Literature, Emerald Group Publishing Limited, vol. 46(1), pages 26-50, June.
  12. Naseh Majidi & Mahdi Shamsi & Farokh Marvasti, 2022. "Algorithmic Trading Using Continuous Action Space Deep Reinforcement Learning," Papers 2210.03469, arXiv.org.
  13. Achraf Yahia & Yassine Mouhssine & Abdelkader El Alaoui & Said Ouatik El Alaoui, 2026. "Exploring the role of Artificial Intelligence in Cryptocurrency Evolution: A Systematic Review and Bibliometric Analysis at the Intersection," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 17(2), pages 5600-5647, April.
  14. Nagl, Maximilian, 2024. "Intricacy of cryptocurrency returns," Economics Letters, Elsevier, vol. 239(C).
  15. Huang, Zih-Chun & Sangiorgi, Ivan & Urquhart, Andrew, 2024. "Forecasting Bitcoin volatility using machine learning techniques," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 97(C).
  16. Evangelos Liaras & Michail Nerantzidis & Antonios Alexandridis, 2024. "Machine learning in accounting and finance research: a literature review," Review of Quantitative Finance and Accounting, Springer, vol. 63(4), pages 1431-1471, November.
  17. Alexander Brauneis & Mehmet Sahiner, 2026. "Crypto Volatility Forecasting: Mounting a HAR, Sentiment, and Machine Learning Horserace," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 33(1), pages 379-411, March.
  18. Kui Wang & Jie Wan & Gang Li & Hao Sun, 2022. "A Hybrid Algorithm-Level Ensemble Model for Imbalanced Credit Default Prediction in the Energy Industry," Energies, MDPI, vol. 15(14), pages 1-18, July.
  19. Alvarez-Ramirez, Jose & Espinosa-Paredes, Gilberto & Vernon-Carter, E. Jaime, 2025. "Causal wavelet analysis of the Bitcoin price dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 658(C).
  20. Goodell, John W. & Ben Jabeur, Sami & Saâdaoui, Foued & Nasir, Muhammad Ali, 2023. "Explainable artificial intelligence modeling to forecast bitcoin prices," International Review of Financial Analysis, Elsevier, vol. 88(C).
  21. Liu, Qingfu & Tao, Zhenyi & Tse, Yiuman & Wang, Chuanjie, 2022. "Stock market prediction with deep learning: The case of China," Finance Research Letters, Elsevier, vol. 46(PA).
  22. Jinghua Wang & Geoffrey M. Ngene & Yan Shi & Ann Nduati Mungai, 2023. "An Investigation of the Predictability of Uncertainty Indices on Bitcoin Returns," JRFM, MDPI, vol. 16(10), pages 1-12, October.
  23. Xiaohang Ren & Wenting Jiang & Qiang Ji & Pengxiang Zhai, 2024. "Seeing is believing: Forecasting crude oil price trend from the perspective of images," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(7), pages 2809-2821, November.
  24. Hajek, Petr & Hikkerova, Lubica & Sahut, Jean-Michel, 2023. "How well do investor sentiment and ensemble learning predict Bitcoin prices?," Research in International Business and Finance, Elsevier, vol. 64(C).
  25. Wei Liu & Yoshihisa Suzuki & Shuyi Du, 2024. "Forecasting the Stock Price of Listed Innovative SMEs Using Machine Learning Methods Based on Bayesian optimization: Evidence from China," Computational Economics, Springer;Society for Computational Economics, vol. 63(5), pages 2035-2068, May.
  26. Li, Xingyi & Liu, Zhuang & Liu, Yujun & Zhu, Shushang & Yan, Jingzhou, 2026. "Predicting cryptocurrency returns with machine learning: Evidence from high-dimensional factor modeling," Pacific-Basin Finance Journal, Elsevier, vol. 96(C).
  27. Liu, Weiyi & Zhao, Xiaojuan & Li, Wenjia & Wang, Ye, 2025. "The effect of the cryptocurrency halving event," Pacific-Basin Finance Journal, Elsevier, vol. 94(C).
  28. Ahmed, Walid M.A., 2022. "Robust drivers of Bitcoin price movements: An extreme bounds analysis," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
  29. Liu, Yujun & Li, Zhongfei & Nekhili, Ramzi & Sultan, Jahangir, 2023. "Forecasting cryptocurrency returns with machine learning," Research in International Business and Finance, Elsevier, vol. 64(C).
  30. Hao, Jun & Feng, Qianqian & Yuan, Jiaxin & Sun, Xiaolei & Li, Jianping, 2022. "A dynamic ensemble learning with multi-objective optimization for oil prices prediction," Resources Policy, Elsevier, vol. 79(C).
  31. Samuka Mohanty & Rajashree Dash, 2023. "A New Dual Normalization for Enhancing the Bitcoin Pricing Capability of an Optimized Low Complexity Neural Net with TOPSIS Evaluation," Mathematics, MDPI, vol. 11(5), pages 1-28, February.
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