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Critical Overview of Agent-Based Models for Economics


  • M. Cristelli
  • L. Pietronero
  • A. Zaccaria


We present an overview of some representative Agent-Based Models in Economics. We discuss why and how agent-based models represent an important step in order to explain the dynamics and the statistical properties of financial markets beyond the Classical Theory of Economics. We perform a schematic analysis of several models with respect to some specific key categories such as agents' strategies, price evolution, number of agents, etc. In the conclusive part of this review we address some open questions and future perspectives and highlight the conceptual importance of some usually neglected topics, such as non-stationarity and the self-organization of financial markets.

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  • M. Cristelli & L. Pietronero & A. Zaccaria, 2011. "Critical Overview of Agent-Based Models for Economics," Papers 1101.1847,
  • Handle: RePEc:arx:papers:1101.1847

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    References listed on IDEAS

    1. Alfarano, Simone & Lux, Thomas & Wagner, Friedrich, 2008. "Time variation of higher moments in a financial market with heterogeneous agents: An analytical approach," Journal of Economic Dynamics and Control, Elsevier, vol. 32(1), pages 101-136, January.
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    Cited by:

    1. Yuri Biondi & Pierpaolo Giannoccolo & Serge Galam, 2011. "The formation of share market prices under heterogeneous beliefs and common knowledge," Papers 1105.3228,
    2. Tseng, Jie-Jun & Li, Sai-Ping, 2012. "Quantifying volatility clustering in financial time series," International Review of Financial Analysis, Elsevier, vol. 23(C), pages 11-19.
    3. Zeng, Yayun & Wang, Jun & Xu, Kaixuan, 2017. "Complexity and multifractal behaviors of multiscale-continuum percolation financial system for Chinese stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 364-376.
    4. Aleksejus Kononovicius & Vygintas Gontis & Valentas Daniunas, 2012. "Agent-based Versus Macroscopic Modeling of Competition and Business Processes in Economics and Finance," Papers 1202.3533,, revised Jun 2012.
    5. Gualdi, Stanislao & Tarzia, Marco & Zamponi, Francesco & Bouchaud, Jean-Philippe, 2015. "Tipping points in macroeconomic agent-based models," Journal of Economic Dynamics and Control, Elsevier, vol. 50(C), pages 29-61.
    6. Federico Garzarelli & Matthieu Cristelli & Andrea Zaccaria & Luciano Pietronero, 2011. "Memory effects in stock price dynamics: evidences of technical trading," Papers 1110.5197,
    7. Vygintas Gontis & Aleksejus Kononovicius, 2013. "Fluctuation analysis of the three agent groups herding model," Papers 1305.5958,
    8. Aleksejus Kononovicius & Vygintas Gontis, 2012. "Three-state herding model of the financial markets," Papers 1210.1838,, revised Jan 2013.
    9. repec:spr:jeicoo:v:12:y:2017:i:3:d:10.1007_s11403-016-0173-0 is not listed on IDEAS
    10. Aleksejus Kononovicius & Vygintas Gontis, 2011. "Agent based reasoning for the non-linear stochastic models of long-range memory," Papers 1106.2685,, revised Aug 2011.
    11. Pierre Blanc & Jonathan Donier & Jean-Philippe Bouchaud, 2015. "Quadratic Hawkes processes for financial prices," Papers 1509.07710,
    12. Efstathios Panayi & Gareth Peters, 2015. "Stochastic simulation framework for the Limit Order Book using liquidity motivated agents," Papers 1501.02447,, revised Jan 2015.
    13. repec:wsi:ijfexx:v:02:y:2015:i:02:n:s2424786315500139 is not listed on IDEAS
    14. Aleksejus Kononovicius & Vygintas Gontis, 2015. "Herding interactions as an opportunity to prevent extreme events in financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 88(7), pages 1-6, July.
    15. Jean-Philippe Bouchaud, 2012. "Crises and collective socio-economic phenomena: simple models and challenges," Papers 1209.0453,, revised Dec 2012.
    16. Aleksejus Kononovicius & Julius Ruseckas, 2014. "Continuous transition from the extensive to the non-extensive statistics in an agent-based herding model," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 87(8), pages 1-7, August.
    17. Alexandru Mandes & Peter Winker, 2017. "Complexity and model comparison in agent based modeling of financial markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(3), pages 469-506, October.
    18. Aleksejus Kononovicius & Valentas Daniunas, 2013. "Agent-based and macroscopic modeling of the complex socio-economic systems," Papers 1303.3693,, revised Apr 2013.
    19. Iori, G. & Porter, J., 2012. "Agent-Based Modelling for Financial Markets," Working Papers 12/08, Department of Economics, City University London.
    20. Jan A. Lipski & Ryszard Kutner, 2013. "Agent-Based Stock Market Model with Endogenous Agents' Impact," Papers 1310.0762,, revised Dec 2013.
    21. Aleksejus Kononovicius & Vygintas Gontis, 2014. "Herding interactions as an opportunity to prevent extreme events in financial markets," Papers 1409.8024,, revised May 2015.
    22. Vikram Krishnamurthy & Sujay Bhatt, 2015. "Sequential Detection of Market shocks using Risk-averse Agent Based Models," Papers 1511.01965,
    23. Pietro DeLellis & Franco Garofalo & Francesco Lo Iudice & Elena Napoletano, 2015. "Wealth distribution across communities of adaptive financial agents," Papers 1509.01217,, revised Sep 2015.
    24. Jan A. Lipski & Ryszard Kutner, 2013. "Trust in foreseeing neighbours - a novel threshold model of financial market," Papers 1301.1824,
    25. Aleksejus Kononovicius & Vygintas Gontis, 2013. "Control of the socio-economic systems using herding interactions," Papers 1309.6105,, revised Feb 2014.

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