3 papers
q-fin.TR2025
JaxMARL-HFT: GPU-Accelerated Large-Scale Multi-Agent Reinforcement Learning for High-Frequency Trading
Valentin Mohl, Sascha Frey, Reuben Leyland +6
Agent-based modelling (ABM) approaches for high-frequency financial markets are difficult to calibrate and validate, partly due to the large parameter space created by defining fix…
q-fin.TR2025
Painting the market: generative diffusion models for financial limit order book simulation and forecasting
Alfred Backhouse, Kang Li, Jakob Foerster +2
Simulating limit order books (LOBs) has important applications across forecasting and backtesting for financial market data. However, deep generative models struggle in this contex…
cs.LG2025
LOB-Bench: Benchmarking Generative AI for Finance -- an Application to Limit Order Book Data
Peer Nagy, Sascha Frey, Kang Li +5
While financial data presents one of the most challenging and interesting sequence modelling tasks due to high noise, heavy tails, and strategic interactions, progress in this area…