Zohreh Karimi - Department of Electrical and Computer Engineering Kharazmi University Tehran, Iran
Homa ghaleh - Faculty of Civil Engineering K. N. Toosi University Tehran, Iran

This paper reviews current research on the use of deep reinforcement learning and machine learning in cryptocurrency market making. The objective of these studies is to identify profitable trading strategies for market-making in cryptocurrency exchanges. In order to forecast market prices, gauge market liquidity, and improve market-making strategies, several models and algorithms are used in the studies. According to the research, deep reinforcement learning and machine learning techniques have shown promise in increasing the effectiveness and profitability of cryptocurrency market making. However, the studies highlight the need for further research to improve the robustness and scalability of these approaches for real-world applications.

cryptocurrency, market maker, machine learning, deep learning, reinforcement learning, artificial intelligence