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On the Design of Artificial Stock Markets

Author

Listed:
  • Boer-Sorban, K.
  • de Bruin, A.
  • Kaymak, U.

Abstract

Artificial stock markets are designed with the aim to study and understand market dynamics by representing (part of) real stock markets. Since there is a large variety of real stock markets with several partially observable elements and hidden processes, artificial markets differ regarding their structure and implementation. In this paper we analyze to what degree current artificial stock markets reflect the workings of real stock markets. In order to conduct this analysis we set up a list of factors which influence market dynamics and are as a consequence important to consider for designing market models. We differentiate two categories of factors: general, well-defined aspects that characterize the organization of a market and hidden aspects that characterize the functioning of the markets and the behaviour of the traders.

Suggested Citation

  • Boer-Sorban, K. & de Bruin, A. & Kaymak, U., 2005. "On the Design of Artificial Stock Markets," ERIM Report Series Research in Management ERS-2005-001-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
  • Handle: RePEc:ems:eureri:1900
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    References listed on IDEAS

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    1. Brock, William A. & Hommes, Cars H., 1998. "Heterogeneous beliefs and routes to chaos in a simple asset pricing model," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1235-1274, August.
    2. Madhavan, Ananth, 2000. "Market microstructure: A survey," Journal of Financial Markets, Elsevier, vol. 3(3), pages 205-258, August.
    3. Chen, Shu-Heng & Yeh, Chia-Hsuan, 2001. "Evolving traders and the business school with genetic programming: A new architecture of the agent-based artificial stock market," Journal of Economic Dynamics and Control, Elsevier, vol. 25(3-4), pages 363-393, March.
    4. Raberto, Marco & Cincotti, Silvano & Focardi, Sergio M. & Marchesi, Michele, 2001. "Agent-based simulation of a financial market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(1), pages 319-327.
    5. C. H. Hommes, 2001. "Financial markets as nonlinear adaptive evolutionary systems," Quantitative Finance, Taylor & Francis Journals, vol. 1(1), pages 149-167.
    6. Tesfatsion, Leigh, 2001. "Introduction to the special issue on agent-based computational economics," Journal of Economic Dynamics and Control, Elsevier, vol. 25(3-4), pages 281-293, March.
    7. Eric Smith & J Doyne Farmer & Laszlo Gillemot & Supriya Krishnamurthy, 2003. "Statistical theory of the continuous double auction," Quantitative Finance, Taylor & Francis Journals, vol. 3(6), pages 481-514.
    8. M. Shatner & L. Muchnik & M. Leshno & S. Solomon, 2000. "A Continuous Time Asynchronous Model of the Stock Market; Beyond the LLS Model," Papers cond-mat/0005430, arXiv.org.
    9. Nicholas T. Chan and Christian Shelton, 2001. "An Adaptive Electronic Market-Maker," Computing in Economics and Finance 2001 146, Society for Computational Economics.
    10. repec:adr:anecst:y:2000:i:60:p:04 is not listed on IDEAS
    11. Matassini, Lorenzo & Franci, Fabio, 2001. "On financial markets trading," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 289(3), pages 526-542.
    12. Franci, Fabio & Marschinski, Robert & Matassini, Lorenzo, 2001. "Learning the optimal trading strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 294(1), pages 213-225.
    13. Chen, Shu-Heng & Lux, Thomas & Marchesi, Michele, 2001. "Testing for non-linear structure in an artificial financial market," Journal of Economic Behavior & Organization, Elsevier, vol. 46(3), pages 327-342, November.
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    Citations

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    Cited by:

    1. Boer-Sorban, K. & Kaymak, U. & de Bruin, A., 2005. "A Modular Agent-Based Environment for Studying Stock Markets," ERIM Report Series Research in Management ERS-2005-017-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    2. Lect. Aurora Murgea Ph. D, 2010. "Classical Lassical And Behavioural Finance In Investor Decision," Annals of University of Craiova - Economic Sciences Series, University of Craiova, Faculty of Economics and Business Administration, vol. 2(38), pages 1-12, May.
    3. Lovric, M. & Kaymak, U. & Spronk, J., 2008. "A Conceptual Model of Investor Behavior," ERIM Report Series Research in Management ERS-2008-030-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    4. Boer-Sorban, K. & Kaymak, U. & Spiering, J., 2006. "From Discrete-Time Models to Continuous-Time, Asynchronous Models of Financial Markets," ERIM Report Series Research in Management ERS-2006-009-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    More about this item

    Keywords

    agent-based computational economics; artificial stock markets; financial markets; market microstructure; uncertainty modeling;

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • M - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics
    • M11 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Production Management
    • R4 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics

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