Development of a Cryptocurrency Trading Strategy Using Machine Learning Methods
( Pp. 11-21)
More about authors
Mikhaiylova Svetlana S.
Dr. Sci. (Econ.), Associate Professor; Professor, Department of Data Analysis and Machine Learning, Faculty of Information Technologyand and Big Data Analysis
Financial University under the Government of the Russian Federation
Moscow, Russian Federation Sabirova Sabina A. Faculty of Information Technology and Big Data Analysis; Financial University under the Government of the Russian; Moscow, Russian Federation.
Financial University under the Government of the Russian Federation
Moscow, Russian Federation Sabirova Sabina A. Faculty of Information Technology and Big Data Analysis; Financial University under the Government of the Russian; Moscow, 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.
How to Cite:
Mikhaiylova S.S., Sabirova S.A. Development of a Cryptocurrency Trading Strategy Using Machine Learning Methods. Computational Nanotechnology. 2024. Vol. 11. No. 2. Pp. 11–21. (In Rus.). DOI: 10.33693/2313-223X-2024-11-2-11-21. EDN: MGSSER
Reference list:
Belova E., Okorokov D. Technical analysis of financial markets. Tutorial. Litrov, 2021.
Safiullin M.A., Elshin L.A., Abdukaeva A.A. Development of a stochastic model for medium-term forecasting of the cryptocurrency exchange rate (according to the scenario). Finance and Credit. 2018. Vol. 24. Issue 17. Pp. 1046–1060. (In Rus.)
Avdeev A.V. Comparison of types of technical analysis indicators and selection of logical categories of indicators for further use in algorithms of the stock exchange trading system. News of Tula State University. Economic and Legal Sciences. 2019. No. 2. Pp. 12–18.
Ostrinskaya L.I., Stragis A.Yu. Optimization of strategies when working in financial markets. Omsk Scientific Bulletin. 2005. No. 2 (31). Pp. 194–197. (In Rus.)
Pershin A.D. Development of trading thirds of cryptocurrencies to determine entry and exit points of trading positions based on machine learning algorithms. Moscow, 2023.
Bolshakov S.N., Kim O.L. Trading strategies of digital currencies on cryptobexchanges. Regional Problems of Economic Transformation. 2022. No. 2 (136). Pp. 82–90. (In Rus.)
John K., O'Hara M., Saleh F. Bitcoin and more. Annual Review of Financial Economics. 2022. Vol. 14. Pp. 95–115. (In Rus.)
Ferdiansyah. Research on Bitcoin stock market forecasting: Methods, techniques and tools. Annual research seminar for graduate students. April 10–11, 2019, Universiti Teknologi Malaysia, Johor Bahru, Skudai.
Giudici G., Milne A., Vinogradov D. Cryptocurrencies: market analysis and prospects. Journal of Economics, Industry and Business. 2020. No. 47. P. 118. URL: https://doi.org/10.1007/s40812-019-00138-6.
Safiullin M.A., Elshin L.A., Abdukaeva A.A. Development of a stochastic model for medium-term forecasting of the cryptocurrency exchange rate (according to the scenario). Finance and Credit. 2018. Vol. 24. Issue 17. Pp. 1046–1060. (In Rus.)
Avdeev A.V. Comparison of types of technical analysis indicators and selection of logical categories of indicators for further use in algorithms of the stock exchange trading system. News of Tula State University. Economic and Legal Sciences. 2019. No. 2. Pp. 12–18.
Ostrinskaya L.I., Stragis A.Yu. Optimization of strategies when working in financial markets. Omsk Scientific Bulletin. 2005. No. 2 (31). Pp. 194–197. (In Rus.)
Pershin A.D. Development of trading thirds of cryptocurrencies to determine entry and exit points of trading positions based on machine learning algorithms. Moscow, 2023.
Bolshakov S.N., Kim O.L. Trading strategies of digital currencies on cryptobexchanges. Regional Problems of Economic Transformation. 2022. No. 2 (136). Pp. 82–90. (In Rus.)
John K., O'Hara M., Saleh F. Bitcoin and more. Annual Review of Financial Economics. 2022. Vol. 14. Pp. 95–115. (In Rus.)
Ferdiansyah. Research on Bitcoin stock market forecasting: Methods, techniques and tools. Annual research seminar for graduate students. April 10–11, 2019, Universiti Teknologi Malaysia, Johor Bahru, Skudai.
Giudici G., Milne A., Vinogradov D. Cryptocurrencies: market analysis and prospects. Journal of Economics, Industry and Business. 2020. No. 47. P. 118. URL: https://doi.org/10.1007/s40812-019-00138-6.
Keywords:
cryptocurrency, Bitcoin, trading strategies, machine learning, moving averages, technical analysis, trading signals.
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