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A Gated Recurrent Unit Approach to Bitcoin Price Prediction

Citations

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Cited by:

  1. 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.
  2. Jujie Wang & Yinan Liao & Zhenzhen Zhuang & Dongming Gao, 2021. "An Optimal Weighted Combined Model Coupled with Feature Reconstruction and Deep Learning for Multivariate Stock Index Forecasting," Mathematics, MDPI, vol. 9(21), pages 1-20, October.
  3. Parth Daxesh Modi & Kamyar Arshi & Pertami J. Kunz & Abdelhak M. Zoubir, 2023. "A Data-driven Deep Learning Approach for Bitcoin Price Forecasting," Papers 2311.06280, arXiv.org.
  4. Yuze Li & Shangrong Jiang & Yunjie Wei & Shouyang Wang, 2021. "Take Bitcoin into your portfolio: a novel ensemble portfolio optimization framework for broad commodity assets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-26, December.
  5. Nezir Köse & Yunus Emre Gür & Emre Ünal, 2025. "Deep Learning and Machine Learning Insights Into the Global Economic Drivers of the Bitcoin Price," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(5), pages 1666-1698, August.
  6. 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).
  7. García-Figal, Alejandro & García-Borroto, Milton & Lage-Codorniu, Carlos & Mulet, Roberto & Lage-Castellanos, Alejandro, 2025. "Dynamics and predictability in informal currency markets: The case of the Cuban Peso," Emerging Markets Review, Elsevier, vol. 69(C).
  8. Chuen Yik Kang & Chin Poo Lee & Kian Ming Lim, 2022. "Cryptocurrency Price Prediction with Convolutional Neural Network and Stacked Gated Recurrent Unit," Data, MDPI, vol. 7(11), pages 1-13, October.
  9. Laszlo Vancsura & Tibor Tatay & Tibor Bareith, 2024. "Investigating the Role of Activation Functions in Predicting the Price of Cryptocurrencies during Critical Economic Periods," Virtual Economics, The London Academy of Science and Business, vol. 7(4), pages 64-91, December.
  10. Darya Lapitskaya & M. Hakan Eratalay & Rajesh Sharma, 2025. "Prediction of Cryptocurrency Prices with the Momentum Indicators and Machine Learning," Computational Economics, Springer;Society for Computational Economics, vol. 66(3), pages 2483-2501, September.
  11. Pamir & Nadeem Javaid & Saher Javaid & Muhammad Asif & Muhammad Umar Javed & Adamu Sani Yahaya & Sheraz Aslam, 2022. "Synthetic Theft Attacks and Long Short Term Memory-Based Preprocessing for Electricity Theft Detection Using Gated Recurrent Unit," Energies, MDPI, vol. 15(8), pages 1-20, April.
  12. Pedro Reis & Ana Paula Serra & Jo~ao Gama, 2025. "The Role of Deep Learning in Financial Asset Management: A Systematic Review," Papers 2503.01591, arXiv.org.
  13. Zeyd Boukhers & Azeddine Bouabdallah & Cong Yang & Jan Jurjens, 2022. "Beyond Trading Data: The Hidden Influence of Public Awareness and Interest on Cryptocurrency Volatility," Papers 2202.08967, arXiv.org, revised Oct 2024.
  14. Shahriari, Zahra & Nazarimehr, Fahimeh & Rajagopal, Karthikeyan & Jafari, Sajad & Perc, Matjaž & Svetec, Milan, 2022. "Cryptocurrency price analysis with ordinal partition networks," Applied Mathematics and Computation, Elsevier, vol. 430(C).
  15. Gyana Ranjan Patra & Mihir Narayan Mohanty, 2023. "Price Prediction of Cryptocurrency Using a Multi-Layer Gated Recurrent Unit Network with Multi Features," Computational Economics, Springer;Society for Computational Economics, vol. 62(4), pages 1525-1544, December.
  16. László Vancsura & Tibor Tatay & Tibor Bareith, 2025. "Navigating AI-Driven Financial Forecasting: A Systematic Review of Current Status and Critical Research Gaps," Forecasting, MDPI, vol. 7(3), pages 1-49, July.
  17. 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.
  18. Fan Fang & Carmine Ventre & Michail Basios & Leslie Kanthan & David Martinez-Rego & Fan Wu & Lingbo Li, 2022. "Cryptocurrency trading: a comprehensive survey," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-59, December.
  19. Naseh Majidi & Mahdi Shamsi & Farokh Marvasti, 2022. "Algorithmic Trading Using Continuous Action Space Deep Reinforcement Learning," Papers 2210.03469, arXiv.org.
  20. Huang, Chiou-Jye & Shen, Yamin & Kuo, Ping-Huan & Chen, Yung-Hsiang, 2022. "Novel spatiotemporal feature extraction parallel deep neural network for forecasting confirmed cases of coronavirus disease 2019," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
  21. 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.
  22. 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.
  23. Konstantinos N. Konstantakis & Panayotis G. Michaelides & Panos Xidonas & Arsenios-Georgios N. Prelorentzos & Aristeidis Samitas, 2025. "Responsible artificial intelligence for measuring efficiency: a neural production specification," Annals of Operations Research, Springer, vol. 354(1), pages 399-425, November.
  24. Będowska-Sójka, Barbara & Wójcik, Piotr & Pele, Daniel Traian, 2026. "Early warning systems for cryptocurrency markets: Predicting ‘zombie’ assets using machine learning," The North American Journal of Economics and Finance, Elsevier, vol. 81(C).
  25. Prosper Lamothe-Fernández & David Alaminos & Prosper Lamothe-López & Manuel A. Fernández-Gámez, 2020. "Deep Learning Methods for Modeling Bitcoin Price," Mathematics, MDPI, vol. 8(8), pages 1-13, July.
  26. Tej Bahadur Shahi & Ashish Shrestha & Arjun Neupane & William Guo, 2020. "Stock Price Forecasting with Deep Learning: A Comparative Study," Mathematics, MDPI, vol. 8(9), pages 1-15, August.
  27. Federico Cini & Annalisa Ferrari, 2024. "A Darwinian Approach via ML to the Analysis of Cryptocurrencies’ Returns," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 14(6), pages 1-6.
  28. Pawan Kumar Singh & Alok Kumar Pandey & S. C. Bose, 2023. "A new grey system approach to forecast closing price of Bitcoin, Bionic, Cardano, Dogecoin, Ethereum, XRP Cryptocurrencies," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(3), pages 2429-2446, June.
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