3 papers
cs.LG2026
FlowLOB: Efficient and Controllable Limit Order Book Generation with Flow Matching
Zhuohan Wang, Andreea Bacalum, Ollie Olby +2
Limit order book (LOB) simulators are most useful to practitioners when they combine realistic market dynamics, computationally efficient sampling, controllable scenario generation…
q-fin.CP2026
LOB-ID: Evaluating Synthetic Market Data by Inception Distances
Andreea Bacalum, Zhuohan Wang, Ollie Olby +2
Generative models of limit orderbook (LOB) data have advanced rapidly, but their evaluation often focuses on stylised facts and selected market statistics. These measures provide u…
q-fin.CP2025
Right Place, Right Time: Market Simulation-based RL for Execution Optimisation
Ollie Olby, Andreea Bacalum, Rory Baggott +1
Execution algorithms are vital to modern trading, they enable market participants to execute large orders while minimising market impact and transaction costs. As these algorithms…