M3模型可生成真实市场交易轨迹，模拟订单流与流动性动态交互。
M3: A State-Event Generative Foundation Model for Market Microstructure Dynamics
- 联合建模订单事件与订单簿状态，捕捉市场微观结构动态
- 在真实股票数据上训练，能复现关键市场规律并预测未来轨迹
- 适合金融仿真、压力测试与市场冲击分析等实际应用
市场微观结构模拟旨在刻画电子金融市场中流动性、价格和订单流的演化过程。由于市场数据仅呈现单一实现路径，许多重要问题本质上是反事实的，需要真实的轨迹级模拟。现有金融生成模型常孤立地建模订单事件与市场状态（如限价单簿），忽视了订单流与流动性之间的动态互动。本文提出M3（Market Microstructure Model），一种面向市场微观结构动态的状态-事件生成基础模型。M3能够生成未来的订单流轨迹，同时考虑订单事件与限价单簿流动性之间的动态交互。模型在大规模订单级真实股票市场数据上训练，展现出可预测的缩放行为，复现了关键市场典型事实，并支持预测、压力测试和市场影响分析等实用仿真应用。结果表明，该模型为微观结构层面的反事实市场模拟提供了一种可扩展的基础模型范式。
原文摘要 · Abstract (English)
Market microstructure simulation aims to model how liquidity, prices, and order flow evolve in electronic financial markets. Since market data reveal only one realized trajectory, many important questions are inherently counterfactual and require realistic trajectory-level simulation. Existing financial generative models, however, often model order events and market states, such as the LOB, in isolation, overlooking the dynamic interaction between order flow and liquidity in market microstructure. We propose the \textbf{M3} (\underline{M}arket \underline{M}icrostructure \underline{M}odel), a state-event generative foundation model for market microstructure dynamics. \textbf{M3} learns to generate future order-flow trajectories, while accounting for the evolving interaction between order events and limit-order-book liquidity. Trained on large-scale order-level real stock market data, \textbf{M3} exhibits predictable scaling behavior, reproduces key market stylized facts, and enables practical simulation-based applications including forecasting, stress testing, and market-impact analysis. These results suggest a scalable foundation-model paradigm for counterfactual market simulation at the microstructure level.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。