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A Comparative Study of Bitcoin Price Prediction Using Deep Learning

Citations

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Cited by:

  1. Aidin Zehtab-Salmasi & Ali-Reza Feizi-Derakhshi & Narjes Nikzad-Khasmakhi & Meysam Asgari-Chenaghlu & Saeideh Nabipour, 2023. "Multimodal Price Prediction," Annals of Data Science, Springer, vol. 10(3), pages 619-635, June.
  2. Ren, Yi-Shuai & Ma, Chao-Qun & Kong, Xiao-Lin & Baltas, Konstantinos & Zureigat, Qasim, 2022. "Past, present, and future of the application of machine learning in cryptocurrency research," Research in International Business and Finance, Elsevier, vol. 63(C).
  3. Nagula, Pavan Kumar & Alexakis, Christos, 2022. "A new hybrid machine learning model for predicting the bitcoin (BTC-USD) price," Journal of Behavioral and Experimental Finance, Elsevier, vol. 36(C).
  4. Ruiguang Li & Liehuang Zhu & Chao Li & Fudong Wu & Dawei Xu, 2023. "BNS: A Detection System to Find Nodes in the Bitcoin Network," Mathematics, MDPI, vol. 11(24), pages 1-14, December.
  5. Bartosz Bieganowski & Robert 'Slepaczuk, 2024. "Supervised Autoencoders with Fractionally Differentiated Features and Triple Barrier Labelling Enhance Predictions on Noisy Data," Papers 2411.12753, arXiv.org, revised Nov 2024.
  6. Hakan Pabuccu & Serdar Ongan & Ayse Ongan, 2023. "Forecasting the movements of Bitcoin prices: an application of machine learning algorithms," Papers 2303.04642, arXiv.org.
  7. Mingzhe Wei & Georgios Sermpinis & Charalampos Stasinakis, 2023. "Forecasting and trading Bitcoin with machine learning techniques and a hybrid volatility/sentiment leverage," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 852-871, July.
  8. Surinder Singh Khurana & Parvinder Singh & Naresh Kumar Garg, 2024. "OG-CAT: A Novel Algorithmic Trading Alternative to Investment in Crypto Market," Computational Economics, Springer;Society for Computational Economics, vol. 63(5), pages 1735-1756, May.
  9. Isabela Ruiz Roque da Silva & Eli Hadad Junior & Pedro Paulo Balbi, 2022. "Cryptocurrencies trading algorithms: A review," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1661-1668, December.
  10. Serdar Arslan, 2025. "Bitcoin Price Prediction Using Sentiment Analysis and Empirical Mode Decomposition," Computational Economics, Springer;Society for Computational Economics, vol. 65(4), pages 2227-2248, April.
  11. Oluwadamilare Omole & David Enke, 2024. "Deep learning for Bitcoin price direction prediction: models and trading strategies empirically compared," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-26, December.
  12. 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).
  13. Ibanga Kpereobong Friday & Sarada Prasanna Pati & Debahuti Mishra & Pradeep Kumar Mallick & Sachin Kumar, 2025. "CAGTRADE: Predicting Stock Market Price Movement with a CNN-Attention-GRU Model," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 32(2), pages 583-608, June.
  14. Zi Ye & Yinxu Wu & Hui Chen & Yi Pan & Qingshan Jiang, 2022. "A Stacking Ensemble Deep Learning Model for Bitcoin Price Prediction Using Twitter Comments on Bitcoin," Mathematics, MDPI, vol. 10(8), pages 1-21, April.
  15. David L. John & Sebastian Binnewies & Bela Stantic, 2024. "Cryptocurrency Price Prediction Algorithms: A Survey and Future Directions," Forecasting, MDPI, vol. 6(3), pages 1-35, August.
  16. Esam Mahdi & Carlos Martin-Barreiro & Xavier Cabezas, 2025. "A Novel Hybrid Approach Using an Attention-Based Transformer + GRU Model for Predicting Cryptocurrency Prices," Mathematics, MDPI, vol. 13(9), pages 1-19, April.
  17. Nicolás Magner & Nicolás Hardy, 2022. "Cryptocurrency Forecasting: More Evidence of the Meese-Rogoff Puzzle," Mathematics, MDPI, vol. 10(13), pages 1-27, July.
  18. Rico-Peña, Juan Jesús & Arguedas-Sanz, Raquel & López-Martin, Carmen, 2023. "Models used to characterise blockchain features. A systematic literature review and bibliometric analysis," Technovation, Elsevier, vol. 123(C).
  19. Dinggao Liu & Zhenpeng Tang & Yi Cai, 2022. "A Hybrid Model for China’s Soybean Spot Price Prediction by Integrating CEEMDAN with Fuzzy Entropy Clustering and CNN-GRU-Attention," Sustainability, MDPI, vol. 14(23), pages 1-22, November.
  20. Bartosz Bieganowski & Robert Slepaczuk, 2024. "Supervised Autoencoder MLP for Financial Time Series Forecasting," Papers 2404.01866, arXiv.org, revised Jun 2024.
  21. Sudersan Behera & Sarat Chandra Nayak & A. V. S. Pavan Kumar, 2024. "Evaluating the Performance of Metaheuristic Based Artificial Neural Networks for Cryptocurrency Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 64(2), pages 1219-1258, August.
  22. Ullah, Subhan & Attah-Boakye, Rexford & Adams, Kweku & Zaefarian, Ghasem, 2022. "Assessing the influence of celebrity and government endorsements on bitcoin’s price volatility," Journal of Business Research, Elsevier, vol. 145(C), pages 228-239.
  23. Gil Cohen, 2022. "Algorithmic Trading and Financial Forecasting Using Advanced Artificial Intelligence Methodologies," Mathematics, MDPI, vol. 10(18), pages 1-13, September.
  24. Yuze Li & Shangrong Jiang & Xuerong Li & Shouyang Wang, 2022. "Hybrid data decomposition-based deep learning for Bitcoin prediction and algorithm trading," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-24, December.
  25. Armand Mihai Cismaru, 2024. "DeepTraderX: Challenging Conventional Trading Strategies with Deep Learning in Multi-Threaded Market Simulations," Papers 2403.18831, arXiv.org.
  26. Duygu Ider & Stefan Lessmann, 2022. "Forecasting Cryptocurrency Returns from Sentiment Signals: An Analysis of BERT Classifiers and Weak Supervision," Papers 2204.05781, arXiv.org, revised Mar 2023.
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