28 citations · 79 across the 23 of their papers we have counts for
24 papers
EarnHFT: Efficient Hierarchical Reinforcement Learning for High Frequency Trading
Molei Qin, Shuo Sun, Wentao Zhang +3
High-frequency trading (HFT) uses computer algorithms to make trading decisions in short time scales (e.g., second-level), which is widely used in the Cryptocurrency (Crypto) marke…
Market-GAN: Adding Control to Financial Market Data Generation with Semantic Context
Haochong Xia, Shuo Sun, Xinrun Wang +1
Financial simulators play an important role in enhancing forecasting accuracy, managing risks, and fostering strategic financial decision-making. Despite the development of financi…
IMM: An Imitative Reinforcement Learning Approach with Predictive Representation Learning for Automatic Market Making
Hui Niu, Siyuan Li, Jiahao Zheng +4
Market making (MM) has attracted significant attention in financial trading owing to its essential function in ensuring market liquidity. With strong capabilities in sequential dec…
Controlling Type Confounding in Ad Hoc Teamwork with Instance-wise Teammate Feedback Rectification
Dong Xing, Pengjie Gu, Qian Zheng +5
Ad hoc teamwork requires an agent to cooperate with unknown teammates without prior coordination. Many works propose to abstract teammate instances into high-level representation o…
Synapse: Trajectory-as-Exemplar Prompting with Memory for Computer Control
Longtao Zheng, Rundong Wang, Xinrun Wang +1
Building agents with large language models (LLMs) for computer control is a burgeoning research area, where the agent receives computer states and performs actions to complete comp…
State Regularized Policy Optimization on Data with Dynamics Shift
Zhenghai Xue, Qingpeng Cai, Shuchang Liu +4
In many real-world scenarios, Reinforcement Learning (RL) algorithms are trained on data with dynamics shift, i.e., with different underlying environment dynamics. A majority of cu…