MarS：由生成式基础模型驱动的金融市场模拟引擎
MarS: a Financial Market Simulation Engine Powered by Generative Foundation Model
AI总结：
本文提出订单级生成式基础模型 LMM，并据此构建金融市场模拟引擎 MarS，以实现真实、交互、可控的订单生成并支持预测、检测、分析和智能体训练。
摘要：
生成式模型旨在模拟从文本生成到视觉效果等不同情境下各类行动的真实效果。尽管人们在构建真实世界模拟器方面付出了巨大努力，但生成式模型在金融市场等虚拟世界中的应用仍未得到充分探索。在金融市场中，生成式模型可以模拟具有各种行为的参与者所产生的复杂市场效应，使其能够在不同市场条件下进行交互，并在没有金融风险的情况下训练策略。这种模拟依赖于金融市场中最细粒度的结构化数据（例如订单），从而构建最精细的真实模拟。我们提出了 Large Market Model（LMM，大型市场模型），这是一种用于金融市场模拟的订单级生成式基础模型，类似于数字世界中的语言建模。我们由 LMM 驱动的金融 Market Simulation engine（MarS，市场模拟引擎）满足了真实、交互式且可控的订单生成这一领域特定需求。关键观察结果包括：LMM 在数据规模和模型复杂度方面具有很强的可扩展性，而 MarS 在带有市场冲击的受控生成中表现出稳健且实用的真实性。我们展示了 MarS 作为预测工具、检测系统、分析平台和智能体训练环境的用途，从而证明 MarS 对多种金融应用具有“范式转变”的潜力。我们在 https://github.com/microsoft/MarS/ 发布 MarS 的代码。
英文摘要：
Generative models aim to simulate realistic effects of various actions across different contexts, from text generation to visual effects. Despite significant efforts to build real-world simulators, the application of generative models to virtual worlds, like financial markets, remains under-explored. In financial markets, generative models can simulate complex market effects of participants with various behaviors, enabling interaction under different market conditions, and training strategies without financial risk. This simulation relies on the finest structured data in financial market like orders thus building the finest realistic simulation. We propose Large Market Model (LMM), an order-level generative foundation model, for financial market simulation, akin to language modeling in the digital world. Our financial Market Simulation engine (MarS), powered by LMM, addresses the domain-specific need for realistic, interactive and controllable order generation. Key observations include LMM's strong scalability across data size and model complexity, and MarS's robust and practicable realism in controlled generation with market impact. We showcase MarS as a forecast tool, detection system, analysis platform, and agent training environment, thus demonstrating MarS's "paradigm shift" potential for a variety of financial applications. We release the code of MarS at https://github.com/microsoft/MarS/.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
