Development of a Cryptocurrency Trading Strategy Using Machine Learning Methods
- Авторлар: Mikhaiylova S.S.1, Sabirova S.A.1
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Мекемелер:
- Financial University under the Government of the Russian Federation
- Шығарылым: Том 11, № 2 (2024)
- Беттер: 11-21
- Бөлім: ИСКУССТВЕННЫЙ ИНТЕЛЛЕКТ И МАШИННОЕ ОБУЧЕНИЕ
- URL: https://journals.eco-vector.com/2313-223X/article/view/635808
- DOI: https://doi.org/10.33693/2313-223X-2024-11-2-11-21
- EDN: https://elibrary.ru/MGSSER
- ID: 635808
Дәйексөз келтіру
Ашық рұқсат
Рұқсат берілді
Аннотация
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.
Негізгі сөздер
Толық мәтін
Авторлар туралы
Svetlana Mikhaiylova
Financial University under the Government of the Russian Federation
Хат алмасуға жауапты Автор.
Email: ssmihajlova@fa.ru
ORCID iD: 0000-0001-9183-8519
Dr. Sci. (Econ.), Associate Professor, Professor, Department of Data Analysis and Machine Learning, Faculty of Information Technologyand and Big Data Analysis
Ресей, MoscowSabina Sabirova
Financial University under the Government of the Russian Federation
Email: 202617@edu.fa.ru
Faculty of Information Technology and Big Data Analysis
Ресей, MoscowӘдебиет тізімі
- 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.
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