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The HoneyComb Paradigm for Research on Collective Human Behavior
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Agent-based model with multi-level herding for complex financial systems.

Jun-Jie Chen1, Lei Tan1, Bo Zheng1

  • 11] Department of Physics, Zhejiang University, Hangzhou 310027, China [2] Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing 210093, China.

Scientific Reports
|February 12, 2015
PubMed
Summary
This summary is machine-generated.

This study introduces multi-level herding in agent-based models to explain financial sector structure and volatility clustering. The model successfully replicates empirical market features, revealing herding as the microscopic driver.

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Area of Science:

  • Complex Systems
  • Financial Economics
  • Computational Finance

Background:

  • Financial markets exhibit sector structure and volatility clustering, reflecting spatial and temporal correlations.
  • The microscopic origins of sector structure and simultaneous generation of both features in a single model remain poorly understood.
  • Existing models struggle to integrate spatial (sector) and temporal (volatility) dynamics from a micro-level perspective.

Purpose of the Study:

  • To investigate the microscopic generation mechanism of sector structure and volatility clustering in financial systems.
  • To introduce and analyze a novel multi-level herding interaction mechanism within an agent-based model.
  • To bridge the gap between microscopic agent behavior and macroscopic market phenomena.

Main Methods:

  • Development of an agent-based model incorporating multi-level herding (stock, sector, and market levels) based on past market performance.
  • Proposal of methods to derive key model parameters directly from historical market data, avoiding purely statistical fitting.
  • Simulation of the model using data from the New York and Hong Kong stock exchanges.

Main Results:

  • The agent-based model successfully reproduces emergent sector structure and volatility clustering.
  • Simulated eigenvalue distributions of the cross-correlation matrix align with empirical observations from major stock exchanges.
  • Quantitative evidence supports multi-level herding as the microscopic mechanism driving sector structure formation.

Conclusions:

  • Multi-level herding is identified as the fundamental microscopic driver of sector structure in financial markets.
  • The study provides novel insights into the complex spatio-temporal interactions governing financial systems at the micro-level.
  • The proposed modeling approach offers a framework for understanding emergent market properties from individual agent behaviors.