Forecasting Bitcoin Prices in the Context of the COVID-19 Pandemic Using Machine Learning Approaches
Conference paper
Sontakke, P., Jafari, F., Saeedi, M. and Amirhosseini, M. 2024. Forecasting Bitcoin Prices in the Context of the COVID-19 Pandemic Using Machine Learning Approaches. ICDAM-2023: 4th International Conference on Data Analytics & Management. London, UK 23 - 24 Jun 2023 Springer. https://doi.org/10.1007/978-981-99-6544-1_7
Authors | Sontakke, P., Jafari, F., Saeedi, M. and Amirhosseini, M. |
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Type | Conference paper |
Keywords | Cryptocurrency; Bitcoin Price; Time Series Forecasting; Machine Learning; Technical Indicators; Linear Regression; Support Vector Regression; Extreme Gradient Boosting; Long Short-Term Memory |
Year | 2024 |
Conference | ICDAM-2023: 4th International Conference on Data Analytics & Management |
Publisher | Springer |
Accepted author manuscript | License File Access Level Anyone |
Publication dates | |
13 Jan 2024 | |
Publication process dates | |
Accepted | 17 Mar 2023 |
Deposited | 09 May 2023 |
Journal citation | pp. 81-94 |
ISSN | 2367-3370 |
Book title | Proceedings of Data Analytics and Management: ICDAM 2023, Volume 1 |
Book editor | Swaroop, A. |
Polkowski, Z. | |
Correia, S. D. | |
Virdee, B. | |
ISBN | 9789819965434 |
9789819965441 | |
Digital Object Identifier (DOI) | https://doi.org/10.1007/978-981-99-6544-1_7 |
Web address (URL) of conference proceedings | https://link.springer.com/book/9789819965434 |
Web address (URL) | https://www.icdam-conf.com/ |
Copyright holder | © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. |
Additional information | Use of archived accepted manuscripts (AMs) of non open-access books and chapters are subject to an embargo period and Springer Nature's AM terms of use, which permit users to view, print, copy, download and text and data-mine the content, for the purposes of academic research, subject always to the full conditions of use. Under no circumstances may the AM be shared or distributed under a Creative Commons, or other form of open access license, nor may it be reformatted or enhanced. Final published version available here: https://link.springer.com/chapter/10.1007/978-981-99-6544-1_7 |
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