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Complexity and Model Comparison in Agent Based Modeling of Financial Markets

Author

Listed:
  • Alexandru Mandes

    () (University of Giessen)

  • Peter Winker

    () (University of Giessen)

Abstract

Agent based models of financial markets follow different approaches and might be categorized according to major building blocks used. Such building blocks include agent design, agent evolution, and the price finding mechanism. The performance of agent based models in matching key features of real market processes depends on how these building blocks are selected and combined. For model comparison, both, measures of model fit and model complexity are required. Some suggestions are made on how to measure complexity of agent based models. An application for the foreign exchange market illustrates the potential of this approach.

Suggested Citation

  • Alexandru Mandes & Peter Winker, 2015. "Complexity and Model Comparison in Agent Based Modeling of Financial Markets," MAGKS Papers on Economics 201528, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
  • Handle: RePEc:mar:magkse:201528
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    References listed on IDEAS

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    Cited by:

    1. Alexandru Mandes, 2020. "Impact of Electronic Liquidity Providers Within a High-Frequency Agent-Based Modeling Framework," Computational Economics, Springer;Society for Computational Economics, vol. 55(2), pages 407-450, February.
    2. Yu, Song-min & Fan, Ying & Zhu, Lei & Eichhammer, Wolfgang, 2020. "Modeling the emission trading scheme from an agent-based perspective: System dynamics emerging from firms’ coordination among abatement options," European Journal of Operational Research, Elsevier, vol. 286(3), pages 1113-1128.
    3. Barde, Sylvain, 2016. "Direct comparison of agent-based models of herding in financial markets," Journal of Economic Dynamics and Control, Elsevier, vol. 73(C), pages 329-353.
    4. Sylvain Barde & Sander Van Der Hoog, 2017. "An empirical validation protocol for large-scale agent-based models," Sciences Po publications 17/12, Sciences Po.
    5. Andrea Vandin & Daniele Giachini & Francesco Lamperti & Francesca Chiaromonte, 2020. "Automated and Distributed Statistical Analysis of Economic Agent-Based Models," LEM Papers Series 2020/31, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    6. Thomas Holtfort, 2019. "From standard to evolutionary finance: a literature survey," Management Review Quarterly, Springer, vol. 69(2), pages 207-232, June.
    7. Elizabeth Jane Casabianca & Alessia Lo Turco & Daniela Maggioni, 2021. "Migration And The Structure Of Manufacturing Production. A View From Italian Provinces," Working Papers 448, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.

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    More about this item

    Keywords

    Agent based modeling; model selection; complexity;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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