Agent-Based Modelling of Market Microstructure presents a practical approach to simulating real financial markets using heterogeneous agents that interact in an order book. This article describes how an agent-based model can reproduce price dynamics, liquidity, and volatility formation by combining simple behaviours and advanced trading rules.
The core of the model consists of five types of traders representing different motivations and time horizons: noise traders who generate random orders that contribute microstructure, momentum traders who follow price trends, fundamentalist traders who trade based on estimated intrinsic value, market makers who provide liquidity and adjust spreads, and arbitrageurs who exploit temporary misalignments between assets. The interaction between these profiles generates a dynamic order book where temporary deviations from fundamental value and episodes of higher or lower liquidity emerge.
Market makers play a critical role in the microstructure: they manage bid and ask quotes, control market depth, and help reduce the impact of large trades. In the model, they implement position limits to manage risk and can temporarily suspend liquidity provision in extreme situations or when excessive volatility is detected, reproducing real market protection mechanisms.
To approximate the underlying fundamental value during simulations, Kalman smoothing is used, a filtering technique that estimates a latent variable from noisy observations. The Kalman filter helps fundamentalist traders update their beliefs about the true value of the asset as trading occurs, and allows studying how information and noise affect price formation in the short and medium term.
This type of model enables stress testing, evaluating the impact of new market rules, designing trading strategies, and calibrating autonomous agents before deployment in real environments. They also facilitate integration with artificial intelligence solutions and AI agents to optimise decisions, use reinforcement learning, or evaluate cybersecurity scenarios that affect the integrity of the order book.
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