M.V. Dobrina1, V.К. Kaverina2

1,2 Financial University under the Government of the Russian Federation (Moscow, Russia)

1 MVDobrina@fa.ru, 2 vkkaverina@fa.ru

Now investing is one of the most popular income growth tools. One of the possible attractive investment options is the development of trading robots that can presumably adapt to changing market conditions and provide high returns for investors. The use of reinforcement learning in trading robots is becoming a particularly promising area, as it allows them to effectively analyze and make decisions based on complex data.

Dobrina M.V., Kaverina V.К. Machine learning in trading: a trading robot based on a deep learning model. Neurocomputers. 2024. V. 26. № 6. Р. 49-54. DOI: https://doi.org/10.18127/j19998554-202406-07 (In Russian)

1. Chan E. Algorithmic Trading: Winning Strategies and Their Rationale. John Wiley & Sons. 2013 г. 224 p.
2. Chan E. Quantitative Trading: How to Build Your Own Algorithmic Trading Business. John Wiley & Sons. 2021. 256 p.
3. Dobrina M.V., Alekseko M.D., Cesko E.E. The e-commerce market: the essence and directions of improvement. Materials of the XVII All-Russian Scientific and Practical. Internet conference "Electronic business: problems, development and prospects". 2019. P. 119–122. (In Russian)
4. Dobrina M.V., Shishatsky A.V. Instrumental forecasting methods in the cryptocurrency market. Materials of the XIV International Scientific and Practical Conference "Economic forecasting: models and methods". 2018. P. 131–136. (In Russian)
5. Chebotarev Yu.A. Trading robots on the Russian stock market. Moscow: Smartbook. 2011. 160 p. (In Russian)