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Network hierarchy in Kirman's ant model: fund investment can create systemic risk

  • Alfarano, Simone
  • Milaković, Mishael
  • Raddant, Matthias

Kirman's ant model has been used to characterize the expectation formation of financial investors who are prone to herding. The model's original version suffers from the problem of N-dependence: its ability to replicate the statistical features of financial returns vanishes once the system size N is increased. In a generalized version of the ant model, the network structure connecting agents turns out to determine whether or not the model is N-dependent. We investigate a class of hierarchical networks in the generalized model that presumably reflect the institutional heterogeneity of financial markets. These network structures do overcome the problem of N-dependence, but at the same time they also increase system-wide volatility. Thus network structure becomes an auxiliary source of volatility in addition to the behavioral heterogeneity of interacting agents.

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Paper provided by Christian-Albrechts-University of Kiel, Department of Economics in its series Economics Working Papers with number 2009,09.

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Date of creation: 2009
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Handle: RePEc:zbw:cauewp:200909
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  1. Masanao Aoki, 2006. "Thermodynamic Limits of Macroeconomic or Financial Models: One-and Two-Parameter Poisson-Dirichlet Models," CIRJE F-Series CIRJE-F-445, CIRJE, Faculty of Economics, University of Tokyo.
  2. Kirman, Alan, 1993. "Ants, Rationality, and Recruitment," The Quarterly Journal of Economics, MIT Press, vol. 108(1), pages 137-56, February.
  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. Alfarano, Simone & Lux, Thomas & Wagner, Friedrich, 2006. "Time-variation of higher moments in a financial market with heterogeneous agents: An analytical approach," Economics Working Papers 2006,16, Christian-Albrechts-University of Kiel, Department of Economics.
  5. 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, vol. 26(1), pages 19-49, August.
  6. Russ Wermers, 1999. "Mutual Fund Herding and the Impact on Stock Prices," Journal of Finance, American Finance Association, vol. 54(2), pages 581-622, 04.
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