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Traders’ long-run wealth in an artificial financial market

  • Marco Raberto
  • Silvano Cincott
  • Sergio M. Focardi
  • Michele Marchesi

In this paper, we study the long-run wealth distribution of agents with different trading strategies in the framework of the Genoa Artificial Stock Market.The Genoa market is an agent-based simulated market able to reproduce the main stylised facts observed in financial markets, i.e., fat-tailed distribution of returns and volatility clustering. Various populations of traders have been introduced in a`thermal bath' made by random traders who make random buy and sell decisions constrained by the available limited resources and depending on past price volatility. We study both trend following and trend contrarian behaviour; fundamentalist traders (i.e., traders believing that stocks have a fundamental price depending on factors external to the market) are also investigated. Results show that the strategy alone does not allow forecasting which population will prevail. Trading strategies yield different results in different market conditions. Generally, in a closed market (a market with no money creation process), we find that trend followers lose relevance and money to other populations of traders and eventually disappear, whereas in an open market (a market with money inflows), trend followers can survive, but their strategy is less profitable than the strategy of other populations. Copyright Kluwer Academic Publishers 2003

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Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2002 with number 301.

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Date of creation: 01 Jul 2002
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Handle: RePEc:sce:scecf2:301
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  1. H.E. Roman & M. Porto & N. Giovanardi, 2001. "Anomalous scaling of stock price dynamics within ARCH-models," The European Physical Journal B - Condensed Matter and Complex Systems, Springer, vol. 21(2), pages 155-158, May.
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  8. 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.
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  10. W. Brian Arthur & John H. Holland & Blake LeBaron & Richard Palmer & Paul Taylor, 1996. "Asset Pricing Under Endogenous Expectation in an Artificial Stock Market," Working Papers 96-12-093, Santa Fe Institute.
  11. 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.
  12. Yanhui Liu & Parameswaran Gopikrishnan & Pierre Cizeau & Martin Meyer & Chung-Kang Peng & H. Eugene Stanley, 1999. "The statistical properties of the volatility of price fluctuations," Papers cond-mat/9903369, arXiv.org, revised Mar 1999.
  13. Lux, Thomas, 1997. "Time variation of second moments from a noise trader/infection model," Journal of Economic Dynamics and Control, Elsevier, vol. 22(1), pages 1-38, November.
  14. Zhi-Feng Huang, Sorin Solomon*, 2001. "Power, Levy, Exponential and Gaussian Regimes in Autocatalytic Financial Systems," Computing in Economics and Finance 2001 12, Society for Computational Economics.
  15. Huang, Zhi-Feng & Solomon, Sorin, 2001. "Finite market size as a source of extreme wealth inequality and market instability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 294(3), pages 503-513.
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  17. Rama Cont & Jean-Philippe Bouchaud, 1997. "Herd behavior and aggregate fluctuations in financial markets," Science & Finance (CFM) working paper archive 500028, Science & Finance, Capital Fund Management.
  18. Lux, T. & M. Marchesi, . "Scaling and Criticality in a Stochastic Multi-Agent Model of a Financial Market," Discussion Paper Serie B 438, University of Bonn, Germany, revised Jul 1998.
  19. LeBaron, Blake & Arthur, W. Brian & Palmer, Richard, 1999. "Time series properties of an artificial stock market," Journal of Economic Dynamics and Control, Elsevier, vol. 23(9-10), pages 1487-1516, September.
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