https://doi.org/10.1140/epjb/e20020146
Herd formation and information transmission in a population: non-universal behaviour
1
Department of Mathematical Sciences, Brunel University, Uxbridge, UB8 3PH, UK
2
Department of Applied Physics, South China University of Technology, Guangzhou 510641, PR China
3
Department of Physics, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong
4
Department of Physics, University of Oxford, Clarendon Laboratory, Oxford OX1 3PU, UK
Corresponding author: a phdzheng@scut.edu.cn
Received:
31
December
2001
Published online: 15 May 2002
We present generalized dynamical models describing the sharing of
information, and the corresponding herd behavior, in a population
based on the recent model proposed by Eguíluz and Zimmermann
(EZ) [Phys. Rev. Lett. 85, 5659 (2000)]. The EZ model, which
is a dynamical version of the herd formation model of Cont and
Bouchaud (CB), gives a reasonable model for the formation of
clusters of agents and for actions taken by clusters of agents.
Both the EZ and CB models give a cluster size distribution
characterized by a power law with an exponent . By
introducing a size-dependent probability for dissociation of a
cluster of agents, we show that the exponent characterizing the
cluster size distribution becomes model-dependent and
non-universal, with an exponential cutoff for large cluster sizes.
The actions taken by the clusters of agents generate the price
returns, the distribution of which is also characterized by a
model-dependent exponent. When a size-dependent transaction rate
is introduced instead of a size-dependent dissociation rate, it is
found that the distribution of price returns is characterized by a
model-dependent exponent while the exponent for the cluster-size
distribution remains unchanged. The resulting systems provide
simplified models of a financial market and yield power law
behaviour with an easily tunable exponent.
PACS: 05.65.+b – Self-organized systems / 87.23.Ge – Dynamics of social systems / 02.50.Le – Decision theory and game theory / 05.45.Tp – Time series analysis
© EDP Sciences, Società Italiana di Fisica, Springer-Verlag, 2002