Market Simulator

Market simulators are computational tools designed to recreate the dynamics of financial markets, primarily aiming to test trading strategies and economic theories without real-world risk. Current research heavily utilizes deep learning architectures, including generative adversarial networks (GANs), graph neural networks, and reinforcement learning (RL) agents, often powered by large language models, to generate realistic market behavior and price movements. These advancements enable more sophisticated analyses of market impacts from various factors (e.g., policy changes, agent interactions) and offer valuable insights for both academic research in economics and finance and practical applications in algorithmic trading and risk management.