MacroHFT : Memory augmented context-aware reinforcement learning on high frequency trading

• Main Authors: ZONG, Chuqiao, WANG, Chaojie, QIN, Molei, FENG, Lei, WANG, Xinrun
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Reinforcement learning; High-frequency trading; Dynamic programming; Markov decision processes; Electronic commerce; Artificial Intelligence and Robotics; Management Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/9831; https://ink.library.smu.edu.sg/context/sis_research/article/10831/viewcontent/3637528.3672064.pdf
• Institution: Singapore Management University

High-frequency trading (HFT) that executes algorithmic trading in short time scales, has recently occupied the majority of cryptocurrency market. Besides traditional quantitative trading methods, reinforcement learning (RL) has become another appealing approach for HFT due to its terrific ability of...