Agent-based model of information diffusion in the limit order book trading

2025-08-28

AI Summary

This study investigates how the topology of trader networks drives the emergence of stylized facts—such as volatility clustering and long memory—in limit-order-book markets. Method: Using agent-based modeling, we systematically compare market dynamics generated by zero-intelligence agents operating on scale-free, regular lattice, and Erdős–Rényi network topologies. Contribution/Results: Only under scale-free network interaction do agents—without informational advantages or cognitive sophistication—robustly reproduce key stylized facts; neither other topologies nor non-interacting settings yield them. These findings establish network structure itself as a sufficient generative mechanism for market complexity, introducing a “structure-driven emergence” framework that challenges prevailing paradigms relying on agent intelligence or heterogeneous beliefs. The work provides a parsimonious, topology-centered perspective for understanding endogenous market complexity.

Technology Category

• Multiagent Systems: Agent-Based Simulation and Emergent Behavior
• Cognitive Modeling & Cognitive Systems: Agent Architectures
• Game Theory and Economic Paradigms: Mechanism Design

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Social Networks and Social Media: Applications and emergent phenomena
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

There are multiple explanations for stylized facts in high-frequency trading, including adaptive and informed agents, many of which have been studied through agent-based models. This paper investigates an alternative explanation by examining whether, and under what circumstances, interactions between traders placing limit order book messages can reproduce stylized facts, and what forms of interaction are required. While the agent-based modeling literature has introduced interconnected agents on networks, little attention has been paid to whether specific trading network topologies can generate stylized facts in limit order book markets. In our model, agents are strictly zero-intelligence, with no fundamental knowledge or chartist-like strategies, so that the role of network topology can be isolated. We find that scale-free connectivity between agents reproduces stylized facts observed in markets, whereas no-interaction does not. Our experiments show that regular lattices and Erdos-Renyi networks are not significantly different from the no-interaction baseline. Thus, we provide a completely new, potentially complementary, explanation for the emergence of stylized facts.

Problem

• Examining trader interactions reproduce limit order book stylized facts
• Investigating specific trading network topologies generate market patterns
• Isolating role of network topology without intelligent agent strategies

Innovation

• Agent-based model with zero-intelligence traders
• Scale-free network connectivity reproduces stylized facts
• Isolates network topology role without agent strategies