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Direct calibration and comparison of agent-based herding models of financial markets

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  • Sylvain Barde

Abstract

The present paper aims to test a new model comparison methodology by calibrating and comparing three agent-based models of financial markets on the daily returns of 18 indices. The models chosen for this empirical application are the herding model of Gilli & Winker, its asymmetric version by Alfarano, Lux & Wagner and the more recent model by Franke & Westerhoff, which all share a common lineage to the herding model introduced by Kirman (1993). In addition, standard ARCH processes are included for each financial series to provide a benchmark for the explanatory power of the models. The methodology provides a clear and consistent ranking of the three models. More importantly, it also reveals that the best performing model, Franke & Westerhoff, is generally not distinguishable from an ARCH-type process, suggesting their explanatory power on the data is similar.

Suggested Citation

  • Sylvain Barde, 2015. "Direct calibration and comparison of agent-based herding models of financial markets," Studies in Economics 1507, School of Economics, University of Kent.
    • Handle: RePEc:ukc:ukcedp:1507
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Pruna, Radu T. & Polukarov, Maria & Jennings, Nicholas R., 2018. "Avoiding regret in an agent-based asset pricing model," Finance Research Letters, Elsevier, vol. 24(C), pages 273-277.
    2. Donovan Platt & Tim Gebbie, 2016. "The Problem of Calibrating an Agent-Based Model of High-Frequency Trading," Papers 1606.01495, arXiv.org, revised Mar 2017.
    3. Guerini, Mattia & Moneta, Alessio, 2017. "A method for agent-based models validation," Journal of Economic Dynamics and Control, Elsevier, vol. 82(C), pages 125-141.
    4. Radu T. Pruna & Maria Polukarov & Nicholas R. Jennings, 2020. "Loss aversion in an agent-based asset pricing model," Quantitative Finance, Taylor & Francis Journals, vol. 20(2), pages 275-290, February.
    5. Zhenxi Chen & Thomas Lux, 2018. "Estimation of Sentiment Effects in Financial Markets: A Simulated Method of Moments Approach," Computational Economics, Springer;Society for Computational Economics, vol. 52(3), pages 711-744, October.
    6. Donovan Platt & Tim Gebbie, 2016. "Can Agent-Based Models Probe Market Microstructure?," Papers 1611.08510, arXiv.org, revised Aug 2017.
    7. Radu T. Pruna & Maria Polukarov & Nicholas R. Jennings, 2016. "A new structural stochastic volatility model of asset pricing and its stylized facts," Papers 1604.08824, arXiv.org.

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    More about this item

    Keywords

    Model selection; agent-based models; herding behaviour;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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