MarS: A Financial Market Simultation Engine Powered By Generative Foundation Model

Generative models, while widely applied to simulate realistic effects in diverse domains, have seen limited exploration in virtual financial markets. Addressing this gap, we introduce the Large Market Model (LMM), an order-level generative foundation model designed for financial market simulation, akin to language modeling in the digital sphere. Our Financial Market Simulation engine, MarS, powered by LMM, sets a new standard by enabling realistic, interactive, and controllable order generation. Key insights reveal LMM's scalability with data and complexity, alongside MarS's robust realism and versatility. As a forecast tool, analysis platform, and training environment, MarS demonstrates transformative potential for financial applications. This paradigm shift opens new avenues for safe strategy testing and market behavior analysis, redefining financial simulations. Explore MarS's open-source implementation at https://github.com/microsoft/MarS/.

Weiqing Liu is currently a principal research manager in Machine Learning group in MSR Asia. He has been leading a team focusing on AI for Finance projects for several years. His current research is centered on the RD-Agent (https://github.com/microsoft/rd-agent) and MarS (https://github.com/microsoft/mars) projects. He has authored tens of papers on top conferences. Before joining MSR Asia, he received his B.S. and Ph.D. degrees in Computer Science from the University and Science and Technology of China.