Showing q-fin.CPShow all
3 papers · 1 filter
q-fin.CP2025
FinFlowRL: An Imitation-Reinforcement Learning Framework for Adaptive Stochastic Control in Finance
Yang Li, Zhi Chen
Traditional stochastic control methods in finance struggle in real world markets due to their reliance on simplifying assumptions and stylized frameworks. Such methods typically pe…
q-fin.CP2025
FinFlowRL: An Imitation-Reinforcement Learning Framework for Adaptive Stochastic Control in Finance
Yang Li, Zhi Chen, Steve Y. Yang +1
Traditional stochastic control methods in finance rely on simplifying assumptions that often fail in real world markets. While these methods work well in specific, well defined sce…
q-fin.CP2025
ByteGen: A Tokenizer-Free Generative Model for Orderbook Events in Byte Space
Yang Li, Zhi Chen
Generative modeling of high-frequency limit order book (LOB) dynamics is a critical yet unsolved challenge in quantitative finance, essential for robust market simulation and strat…