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Study of a Market Model with Conservative Exchanges on Complex Networks


  • L. A. Braunstein
  • P. A. Macri
  • J. R. Iglesias


Many models of market dynamics make use of the idea of conservative wealth exchanges among economic agents. A few years ago an exchange model using extremal dynamics was developed and a very interesting result was obtained: a self-generated minimum wealth or poverty line. On the other hand, the wealth distribution exhibited an exponential shape as a function of the square of the wealth. These results have been obtained both considering exchanges between nearest neighbors or in a mean field scheme. In the present paper we study the effect of distributing the agents on a complex network. We have considered archetypical complex networks: Erd\"{o}s-R\'enyi random networks and scale-free networks. The presence of a poverty line with finite wealth is preserved but spatial correlations are important, particularly between the degree of the node and the wealth. We present a detailed study of the correlations, as well as the changes in the Gini coefficient, that measures the inequality, as a function of the type and average degree of the considered networks.

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  • L. A. Braunstein & P. A. Macri & J. R. Iglesias, 2012. "Study of a Market Model with Conservative Exchanges on Complex Networks," Papers 1212.1061,, revised Feb 2013.
  • Handle: RePEc:arx:papers:1212.1061

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    References listed on IDEAS

    1. Garman, Mark B & Klass, Michael J, 1980. "On the Estimation of Security Price Volatilities from Historical Data," The Journal of Business, University of Chicago Press, vol. 53(1), pages 67-78, January.
    2. Kahneman, Daniel & Tversky, Amos, 1979. "Prospect Theory: An Analysis of Decision under Risk," Econometrica, Econometric Society, vol. 47(2), pages 263-291, March.
    3. Garth P. McCormick, 1969. "Communications to the Editor--Exponential Forecasting: Some New Variations," Management Science, INFORMS, vol. 15(5), pages 311-320, January.
    4. Paul C. Tetlock, 2007. "Giving Content to Investor Sentiment: The Role of Media in the Stock Market," Journal of Finance, American Finance Association, vol. 62(3), pages 1139-1168, June.
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    Cited by:

    1. Wang, Xiaoyang & Wang, Ying & Zhu, Lin & Li, Chao, 2016. "A novel approach to characterize information radiation in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 452(C), pages 94-105.
    2. Meng, Xiangyi & Zhang, Jian-Wei & Guo, Hong, 2016. "Quantum Brownian motion model for the stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 452(C), pages 281-288.

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