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On the problem of calibrating an agent based model for financial markets

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  • Annalisa Fabretti

Abstract

Agent based models are very widely used in different disciplines. In financial markets, they can be used to explain well known features called stylised facts and fit statistical properties of data. For this reason, they can model price movements better than standard models using gaussianity. Calibration and validation are essential issues in agent-based modeling. However, calibrating such models is not yet sufficiently considered in the literature. In this paper, a Nelder–Mead simplex algorithm coupled with threshold accepting algorithm (Gilli and Winker in Comput Stat Data Anal 42:299–312, 2003 ) and a genetic algorithm have been implemented to calibrate the model presented by Farmer and Joshi (J Econ Behav Org 49:149–171, 2002 ) and the outcomes have been compared and discussed. The data used are closing prices of S&P500 Composite index and a particular attention has been devoted to the choice of the objective function. Copyright Springer-Verlag 2013

Suggested Citation

  • Annalisa Fabretti, 2013. "On the problem of calibrating an agent based model for financial markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(2), pages 277-293, October.
    • Handle: RePEc:spr:jeicoo:v:8:y:2013:i:2:p:277-293
    DOI: 10.1007/s11403-012-0096-3
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    1. Matteo Richiardi & Roberto Leombruni & Nicole J. Saam & Michele Sonnessa, 2006. "A Common Protocol for Agent-Based Social Simulation," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 9(1), pages 1-15.
    2. Paolo Pellizzari & Arianna Forno, 2007. "A comparison of different trading protocols in an agent-based market," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 2(1), pages 27-43, June.
    3. Di Matteo, T. & Aste, T. & Dacorogna, M.M., 2003. "Scaling behaviors in differently developed markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 183-188.
    4. Tesfatsion, Leigh & Judd, Kenneth L., 2006. "Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics," Staff General Research Papers Archive 10368, Iowa State University, Department of Economics.
    5. Thomas Lux & Michele Marchesi, 1999. "Scaling and criticality in a stochastic multi-agent model of a financial market," Nature, Nature, vol. 397(6719), pages 498-500, February.
    6. Peter Winker & Manfred Gilli & Vahidin Jeleskovic, 2007. "An objective function for simulation based inference on exchange rate data," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 2(2), pages 125-145, December.
    7. Thomas Brenner & Claudia Werker, 2007. "A Taxonomy of Inference in Simulation Models," Computational Economics, Springer;Society for Computational Economics, vol. 30(3), pages 227-244, October.
    8. Farmer, J. Doyne & Joshi, Shareen, 2002. "The price dynamics of common trading strategies," Journal of Economic Behavior & Organization, Elsevier, vol. 49(2), pages 149-171, October.
    9. Leigh Tesfatsion & Kenneth L. Judd (ed.), 2006. "Handbook of Computational Economics," Handbook of Computational Economics, Elsevier, edition 1, volume 2, number 2.
    10. Iryna Veryzhenko & Olivier Brandouy & Philippe Mathieu, 2010. "Agent’s Minimal Intelligence Calibration for Realistic Market Dynamics," Lecture Notes in Economics and Mathematical Systems, in: Marco Li Calzi & Lucia Milone & Paolo Pellizzari (ed.), Progress in Artificial Economics, pages 3-14, Springer.
    11. Robert Marks, 2007. "Validating Simulation Models: A General Framework and Four Applied Examples," Computational Economics, Springer;Society for Computational Economics, vol. 30(3), pages 265-290, October.
    12. Marco Li Calzi & Lucia Milone & Paolo Pellizzari (ed.), 2010. "Progress in Artificial Economics," Lecture Notes in Economics and Mathematical Systems, Springer, number 978-3-642-13947-5, December.
    13. Hommes, Cars H., 2006. "Heterogeneous Agent Models in Economics and Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 23, pages 1109-1186, Elsevier.
    14. Day, Richard H. & Huang, Weihong, 1990. "Bulls, bears and market sheep," Journal of Economic Behavior & Organization, Elsevier, vol. 14(3), pages 299-329, December.
    15. Mike, Szabolcs & Farmer, J. Doyne, 2008. "An empirical behavioral model of liquidity and volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 32(1), pages 200-234, January.
    16. LeBaron, Blake, 2000. "Agent-based computational finance: Suggested readings and early research," Journal of Economic Dynamics and Control, Elsevier, vol. 24(5-7), pages 679-702, June.
    17. Leombruni, Roberto & Richiardi, Matteo, 2005. "Why are economists sceptical about agent-based simulations?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(1), pages 103-109.
    18. Philippe Mathieu & Bruno Beaufils & Olivier Brandouy, 2005. "Artificial Economics," Post-Print hal-00826572, HAL.
    19. Raberto, Marco & Teglio, Andrea & Cincotti, Silvano, 2012. "Debt, deleveraging and business cycles: An agent-based perspective," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 6, pages 1-49.
    20. T. Di Matteo, 2007. "Multi-scaling in finance," Quantitative Finance, Taylor & Francis Journals, vol. 7(1), pages 21-36.
    21. Simone Alfarano & Thomas Lux & Friedrich Wagner, 2005. "Estimation of Agent-Based Models: The Case of an Asymmetric Herding Model," Computational Economics, Springer;Society for Computational Economics, vol. 26(1), pages 19-49, August.
    22. Gilli, M. & Winker, P., 2003. "A global optimization heuristic for estimating agent based models," Computational Statistics & Data Analysis, Elsevier, vol. 42(3), pages 299-312, March.
    23. Pasquale Cirillo & Mauro Gallegati, 2012. "The Empirical Validation of an Agent-based Model," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 38(4), pages 525-547.
    24. Bianchi, Carlo & Cirillo, Pasquale & Gallegati, Mauro & Vagliasindi, Pietro A., 2008. "Validation in agent-based models: An investigation on the CATS model," Journal of Economic Behavior & Organization, Elsevier, vol. 67(3-4), pages 947-964, September.
    25. Carlo Bianchi & Pasquale Cirillo & Mauro Gallegati & Pietro Vagliasindi, 2007. "Validating and Calibrating Agent-Based Models: A Case Study," Computational Economics, Springer;Society for Computational Economics, vol. 30(3), pages 245-264, October.
    26. R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
    27. Delli Gatti, Domenico & Gallegati, Mauro & Giulioni, Gianfranco & Palestrini, Antonio, 2003. "Financial fragility, patterns of firms' entry and exit and aggregate dynamics," Journal of Economic Behavior & Organization, Elsevier, vol. 51(1), pages 79-97, May.
    28. Giorgio Fagiolo & Alessio Moneta & Paul Windrum, 2007. "A Critical Guide to Empirical Validation of Agent-Based Models in Economics: Methodologies, Procedures, and Open Problems," Computational Economics, Springer;Society for Computational Economics, vol. 30(3), pages 195-226, October.
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    More about this item

    Keywords

    Agent based model; Artificial markets; Calibration; Genetic algorithm; C13; C52; G10;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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