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Should Network Structure Matter in Agent-Based Finance?

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  • Alfarano, Simone
  • Milaković, Mishael

Abstract

We derive microscopic foundations for a well-known probabilistic herding model in the agent-based finance literature. Lo and behold, the model is quite robust with respect to behavioral heterogeneity, yet structural heterogeneity, in the sense of an underlying network structure that describes the very feasibility of agent interaction, has a crucial and non-trivial impact on the macroscopic properties of the model. --

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Bibliographic Info

Paper provided by Christian-Albrechts-University of Kiel, Department of Economics in its series Economics Working Papers with number 2008,04.

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Date of creation: 2008
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Handle: RePEc:zbw:cauewp:7023

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Keywords: Herding; networks; mean-field approach; N-dependence;

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References

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  1. P. Gopikrishnan & M. Meyer & L.A.N. Amaral & H.E. Stanley, 1998. "Inverse cubic law for the distribution of stock price variations," The European Physical Journal B - Condensed Matter and Complex Systems, Springer, Springer, vol. 3(2), pages 139-140, July.
  2. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, Elsevier, vol. 1(1), pages 83-106, June.
  3. Lux, Thomas & Schornstein, Sascha, 2005. "Genetic learning as an explanation of stylized facts of foreign exchange markets," Journal of Mathematical Economics, Elsevier, vol. 41(1-2), pages 169-196, February.
  4. repec:att:wimass:9530 is not listed on IDEAS
  5. Aoki,Masanao, 1998. "New Approaches to Macroeconomic Modeling," Cambridge Books, Cambridge University Press, Cambridge University Press, number 9780521637695.
  6. Pagan, Adrian, 1996. "The econometrics of financial markets," Journal of Empirical Finance, Elsevier, Elsevier, vol. 3(1), pages 15-102, May.
  7. Harrison Hong & Jeffrey D. Kubik & Jeremy C. Stein, 2003. "The Neighbor's Portfolio: Word-of-Mouth Effects in the Holdings and Trade of Money Managers," NBER Working Papers 9711, National Bureau of Economic Research, Inc.
  8. I.N. Lobato & N.E. Savin, 1996. "Real and Spurious Long Memory Properties of Stock Market Data," Econometrics, EconWPA 9605004, EconWPA, revised 26 Sep 1996.
  9. Brock, W.A. & Hommes, C.H., 1996. "A Rational Route to Randomness," Working papers, Wisconsin Madison - Social Systems 9530r, Wisconsin Madison - Social Systems.
  10. Simone Alfarano & Thomas Lux & Friedrich Wagner, 2005. "Estimation of Agent-Based Models: The Case of an Asymmetric Herding Model," Computational Economics, Society for Computational Economics, Society for Computational Economics, vol. 26(1), pages 19-49, August.
  11. S. Redner, 1998. "How popular is your paper? An empirical study of the citation distribution," The European Physical Journal B - Condensed Matter and Complex Systems, Springer, Springer, vol. 4(2), pages 131-134, July.
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Cited by:
  1. H. Lamba, 2010. "A queueing theory description of fat-tailed price returns in imperfect financial markets," The European Physical Journal B - Condensed Matter and Complex Systems, Springer, Springer, vol. 77(2), pages 297-304, September.
  2. Thomas Lux, 2008. "Stochastic Behavioral Asset Pricing Models and the Stylized Facts," Working Papers, Warwick Business School, Finance Group wp08-03, Warwick Business School, Finance Group.
  3. Bowden, Mark P., 2012. "Information contagion within small worlds and changes in kurtosis and volatility in financial prices," Journal of Macroeconomics, Elsevier, Elsevier, vol. 34(2), pages 553-566.
  4. Iori, G. & Porter, J., 2012. "Agent-Based Modelling for Financial Markets," Working Papers, Department of Economics, City University London 12/08, Department of Economics, City University London.
  5. Chang, Chia-ling & Chen, Shu-heng, 2011. "Interactions in DSGE models: The Boltzmann-Gibbs machine and social networks approach," Economics Discussion Papers 2011-25, Kiel Institute for the World Economy.

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