28 citations · 79 across the 23 of their papers we have counts for
4 papers · 1 filter
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…
PRUDEX-Compass: Towards Systematic Evaluation of Reinforcement Learning in Financial Markets
Shuo Sun, Molei Qin, Xinrun Wang +1
The financial markets, which involve more than $90 trillion market capitals, attract the attention of innumerable investors around the world. Recently, reinforcement learning in fi…
Quantitative Stock Investment by Routing Uncertainty-Aware Trading Experts: A Multi-Task Learning Approach
Shuo Sun, Rundong Wang, Bo An
Quantitative investment is a fundamental financial task that highly relies on accurate stock prediction and profitable investment decision making. Despite recent advances in deep l…
DeepScalper: A Risk-Aware Reinforcement Learning Framework to Capture Fleeting Intraday Trading Opportunities
Shuo Sun, Wanqi Xue, Rundong Wang +4
Reinforcement learning (RL) techniques have shown great success in many challenging quantitative trading tasks, such as portfolio management and algorithmic trading. Especially, in…