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A Modular Agent-Based Environment for Studying Stock Markets

Author

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

Abstract

Artificial stock markets are built with diffuse priors in mind regarding trading strategies and price formation mechanisms. Diffuse priors are a natural consequence of the unknown relation between the various elements that drive market dynamics and the large variety of market organizations, findings, however, might hold only within the specific market settings. In this paper we propose a framework for building agent-based artificial stock markets. We present the mechanism of the framework based on a previously identified list of organizational and behavioural aspects. Within the framework experiments with arbitrary many trading strategies, acting in various market organizations can be conducted in a flexible way, without changing its architecture. In this way experiments of other artificial stock markets, as well as theoretical models can be replicated and their findings compared. Comparisons of the different experimental results might indicate whether findings are due to traders’ behaviour or to the chosen market structure and could suggest how to improve market quality.

Suggested Citation

  • 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.
  • Handle: RePEc:ems:eureri:1929
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    References listed on IDEAS

    as
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    5. C. H. Hommes, 2001. "Financial markets as nonlinear adaptive evolutionary systems," Quantitative Finance, Taylor & Francis Journals, vol. 1(1), pages 149-167.
    6. Gaunersdorfer, A. & Hommes, C.H. & Wagener, F.O.O., 2000. "Bifurcation Routes to Volatility Clustering," CeNDEF Working Papers 00-04, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    7. Mitchel Y. Abolafia (ed.), 2005. "Markets," Books, Edward Elgar Publishing, number 2788.
    8. Theissen, Erik, 2000. "Market structure, informational efficiency and liquidity: An experimental comparison of auction and dealer markets," Journal of Financial Markets, Elsevier, vol. 3(4), pages 333-363, November.
    9. 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.
    10. William A. Brock & Cars H. Hommes, 1997. "A Rational Route to Randomness," Econometrica, Econometric Society, vol. 65(5), pages 1059-1096, September.
    11. repec:adr:anecst:y:2000:i:60:p:04 is not listed on IDEAS
    12. 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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    Cited by:

    1. 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.

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    More about this item

    Keywords

    agent-based modelling; artificial stock markets; behavioural finance; computational economics; simulatiemodellen;
    All these keywords.

    JEL classification:

    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality
    • M - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D

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