6 citations · 30 across the 12 of their papers we have counts for
12 papers
Unlocking the Forecasting Economy: A Suite of Datasets for the Full Lifecycle of Prediction Market: [Experiments \& Analysis]
Huaiyu Jia, Luofeng Zhou, Wentao Zhang +3
Prediction markets are markets for trading claims on universal future events (e.g., presidential elections). Fueled by a meteoric surge with over $50 billion trading volume, they…
Towards Event-Aware Forecasting in DeFi: Insights from On-chain Automated Market Maker Protocols
Huaiyu Jia, Jiehshun You, Yizhi Luo +2
Automated Market Makers (AMMs), as a core infrastructure of decentralized finance (DeFi), uniquely drive on-chain asset pricing through a deterministic reserve ratio mechanism. Unl…
FineFT: Efficient and Risk-Aware Ensemble Reinforcement Learning for Futures Trading
Molei Qin, Xinyu Cai, Yewen Li +5
Futures are contracts obligating the exchange of an asset at a predetermined date and price, notable for their high leverage and liquidity and, therefore, thrive in the Crypto mark…
A Multimodal Foundation Agent for Financial Trading: Tool-Augmented, Diversified, and Generalist
Wentao Zhang, Lingxuan Zhao, Haochong Xia +10
Financial trading is a crucial component of the markets, informed by a multimodal information landscape encompassing news, prices, and Kline charts, and encompasses diverse tasks s…
Reinforcement Learning with Maskable Stock Representation for Portfolio Management in Customizable Stock Pools
Wentao Zhang, Yilei Zhao, Shuo Sun +5
Portfolio management (PM) is a fundamental financial trading task, which explores the optimal periodical reallocation of capitals into different stocks to pursue long-term profits.…
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…
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…
PrefRec: Recommender Systems with Human Preferences for Reinforcing Long-term User Engagement
Wanqi Xue, Qingpeng Cai, Zhenghai Xue +6
Current advances in recommender systems have been remarkably successful in optimizing immediate engagement. However, long-term user engagement, a more desirable performance metric,…
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…
Reinforcement Learning for Quantitative Trading
Shuo Sun, Rundong Wang, Bo An
Quantitative trading (QT), which refers to the usage of mathematical models and data-driven techniques in analyzing the financial market, has been a popular topic in both academia…