Agent-Based modeling in financial markets: Modeling frameworks, validation challenges, and emerging applications

As financial markets have increasingly exhibited heterogeneity across participants, complex interactions among them, and out-of-equilibrium dynamics, have provided growing interest in agent-based modeling (ABM). Unlike traditional representative-agent models, ABMs generate macro-level market behavior from the bottom up through interactions among adaptive agents. In this paper, we review the development and applications of ABMs in financial markets and provide a structured perspective on the growing literature. Specifically, we reviewed three key design axes—agent heterogeneity, market mechanism fidelity, and interaction topology—and discussed how different modeling assumptions shape the ability of ABMs to reproduce stylized financial market phenomena. We also discussed two emerging domains in which ABMs are increasingly applied: Simulations using LLM-based agents and modeling approaches in green energy finance and climate-related financial systems. Here, we identified the current boundaries of financial ABM research and promising directions for future research.