Optimization of Shopping Strategy in Cryptocurrency Markets Based on Artificial Neural Networks
- Авторлар: Savostyanov A.V.1, Grineva N.V.1
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Мекемелер:
- Financial University under the Government of the Russian Federation
- Шығарылым: Том 20, № 1 (2024)
- Беттер: 141-147
- Бөлім: Mathematical, Statistical and Instrumental Methods in Economics
- URL: https://journals.eco-vector.com/2541-8025/article/view/633378
- EDN: https://elibrary.ru/UNNQIK
- ID: 633378
Дәйексөз келтіру
Ашық рұқсат
Рұқсат берілді
Аннотация
This study is relevant in the context of modern finance, where neural networks play a key role in the analysis and forecasting of price dynamics. The research focuses on identifying buy signals for the BTCUSDT and ETHUSDT trading pairs in the cryptocurrency market. To construct a neural network model that can automate the identification of moments beneficial for purchasing selected assets, various technical analysis indicators and convolutional neural networks (CNN) were used. The research includes an analysis of scientific literature, data collection, indicator selection, signal algorithm development, and the construction of neural network models. The main contribution of this work lies in the development and testing of models capable of predicting buy signals with a high accuracy, confirmed by accuracy indicators of over 92%. The findings of this study can be useful for private investors and financial institutions in forming investment strategies based on machine learning.
Негізгі сөздер
Толық мәтін
Авторлар туралы
Aleksandr Savostyanov
Financial University under the Government of the Russian Federation
Хат алмасуға жауапты Автор.
Email: s.aleks-02@mail.ru
Faculty of Information Technology and Big Data Analysis
Ресей, MoscowNatalia Grineva
Financial University under the Government of the Russian Federation
Email: ngrineva@fa.ru
Cand. Sci. (Econ.), Associate Professor, Associate Professor of the Department of Data Analysis and Machine Learning
Ресей, MoscowӘдебиет тізімі
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