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ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING
Development of a cryptocurrency trading strategy using machine learning methods
S. S. Mikhaylova, S. A. Sabirova Financial University under the Government of the Russian Federation
Abstract:
This article presents the results of a study aimed at forecasting signals for buying and selling Bitcoin cryptocurrency using machine learning models. The conducted analysis included the study of cryptocurrency features and markets, technical analysis, development of trading strategies, application of mathematical methods based on moving averages, and building classification models for buy or sell signals. The results demonstrate the effectiveness of applying machine learning models in modern trading strategies in the cryptocurrency market.
Keywords:
cryptocurrency, Bitcoin, trading strategies, machine learning, moving averages, technical analysis, trading signals.
Citation:
S. S. Mikhaylova, S. A. Sabirova, “Development of a cryptocurrency trading strategy using machine learning methods”, Comp. nanotechnol., 11:2 (2024), 11–21
Linking options:
https://www.mathnet.ru/eng/cn476 https://www.mathnet.ru/eng/cn/v11/i2/p11
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Statistics & downloads: |
Abstract page: | 57 | Full-text PDF : | 24 |
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