English

Power-law exponent of the Bouchaud-M\'ezard model on regular random network

Adaptation and Self-Organizing Systems 2013-08-01 v1 Statistical Finance

Abstract

We study the Bouchaud-M\'ezard model on a regular random network. By assuming adiabaticity and independency, and utilizing the generalized central limit theorem and the Tauberian theorem, we derive an equation that determines the exponent of the probability distribution function of the wealth as xx\rightarrow \infty. The analysis shows that the exponent can be smaller than 2, while a mean-field analysis always gives the exponent as being larger than 2. The results of our analysis are shown to be good agreement with those of the numerical simulations.

Keywords

Cite

@article{arxiv.1307.4821,
  title  = {Power-law exponent of the Bouchaud-M\'ezard model on regular random network},
  author = {Takashi Ichinomiya},
  journal= {arXiv preprint arXiv:1307.4821},
  year   = {2013}
}

Comments

To be pubished in Phys. Rev. E