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Some new results on the Levy, Levy and Solomon microscopic stock market model

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  • Zschischang, Elmar
  • Lux, Thomas

Abstract

We report some findings from our simulations of the Levy, Levy and Solomon microscopic stock market model. Our results cast doubts on some of the results published in the original papers (i.e., chaotic stock price movements). We also point out the possibility of sensitive dependence on initial conditions of the emerging wealth distribution among agents. Extensions of the model set-up show that with varying degrees of risk aversion, the less risk averse traders will tend to dominate the market. Similarly, when introducing a new trader group (or even a single trader) with a constant share of stocks in their portfolio, the latter will eventually take over and marginalize the other groups. The better performance of the more sober investors is in accordance with traditional perceptions in financial economics. Hence, the survival of ‘noise traders’ looking at short-term trends and patterns remains as much of a puzzle in this framework as in the traditional Efficient Market Theory.

Suggested Citation

  • Zschischang, Elmar & Lux, Thomas, 2001. "Some new results on the Levy, Levy and Solomon microscopic stock market model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 291(1), pages 563-573.
  • Handle: RePEc:eee:phsmap:v:291:y:2001:i:1:p:563-573
    DOI: 10.1016/S0378-4371(00)00609-9
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    Citations

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    Cited by:

    1. Gulio Bottazzi & Mikhail Anufriev, 2006. "Price and Wealth Dynamics in a Speculative Market with Generic Procedurally Rational Traders," Working Papers wp06-02, Warwick Business School, Finance Group.
    2. Anufriev, Mikhail & Bottazzi, Giulio & Pancotto, Francesca, 2006. "Equilibria, stability and asymptotic dominance in a speculative market with heterogeneous traders," Journal of Economic Dynamics and Control, Elsevier, vol. 30(9-10), pages 1787-1835.
    3. Thomas Lux, 2009. "Applications of Statistical Physics in Finance and Economics," Chapters,in: Handbook of Research on Complexity, chapter 9 Edward Elgar Publishing.
    4. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2007. "Agent-based Models of Financial Markets," Papers physics/0701140, arXiv.org.
    5. Anufriev, Mikhail & Dindo, Pietro, 2010. "Wealth-driven selection in a financial market with heterogeneous agents," Journal of Economic Behavior & Organization, Elsevier, vol. 73(3), pages 327-358, March.
    6. Lux, Thomas, 2008. "Applications of statistical physics in finance and economics," Kiel Working Papers 1425, Kiel Institute for the World Economy (IfW).
    7. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2001. "Microscopic Models of Financial Markets," Papers cond-mat/0110354, arXiv.org.
    8. Mikhail Anufriev, 2008. "Wealth-driven competition in a speculative financial market: examples with maximizing agents," Quantitative Finance, Taylor & Francis Journals, vol. 8(4), pages 363-380.
    9. He, Xue-Zhong & Zheng, Min, 2010. "Dynamics of moving average rules in a continuous-time financial market model," Journal of Economic Behavior & Organization, Elsevier, vol. 76(3), pages 615-634, December.
    10. Carl Chiarella & Roberto Dieci & Xue-Zhong He, 2011. "The dynamic behaviour of asset prices in disequilibrium: a survey," International Journal of Behavioural Accounting and Finance, Inderscience Enterprises Ltd, vol. 2(2), pages 101-139.
    11. Mikhail Anufriev & Giulio Bottazzi, 2006. "Behavioral Consistent Market Equilibria under Procedural Rationality," Computing in Economics and Finance 2006 225, Society for Computational Economics.
    12. LeBaron, Blake, 2006. "Agent-based Computational Finance," Handbook of Computational Economics,in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 24, pages 1187-1233 Elsevier.

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