3 papers
cs.AI2026
History Is Not Enough: An Adaptive Dataflow System for Financial Time-Series Synthesis
Haochong Xia, Yao Long Teng, Regan Tan +3
In quantitative finance, the gap between training and real-world performance-driven by concept drift and distributional non-stationarity-remains a critical obstacle for building re…
cs.LG2026
Bayesian Robust Financial Trading with Adversarial Synthetic Market Data
Haochong Xia, Simin Li, Ruixiao Xu +7
Algorithmic trading relies on machine learning models to make trading decisions. Despite strong in-sample performance, these models often degrade when confronted with evolving real…
cs.LG2025
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…