EarnHFT: Efficient hierarchical reinforcement learning for high frequency trading

• المؤلفون الرئيسيون: QIN, Molei, SUN, Shuo, ZHANG, Wentao, XIA, Haochong, WANG, Xinrun, AN, Bo
• التنسيق: text
• اللغة: English
• منشور في: Institutional Knowledge at Singapore Management University 2024
• الموضوعات: Reinforcement Learning; Time-Series/Data Streams; Artificial Intelligence and Robotics; Finance and Financial Management; Numerical Analysis and Scientific Computing
• الوصول للمادة أونلاين: https://ink.library.smu.edu.sg/sis_research/9128; https://ink.library.smu.edu.sg/context/sis_research/article/10131/viewcontent/29384_EarnHFT_pvoa.pdf
• المؤسسة: Singapore Management University

High-frequency trading (HFT) is using computer algorithms to make trading decisions in short time scales (e.g., second-level), which is widely used in the Cryptocurrency (Crypto) market, (e.g., Bitcoin). Reinforcement learning (RL) in financial research has shown stellar performance on many quantita...