Stochastic analysis of an agent-based model
A. Veglio and
M. Marsili
Papers from arXiv.org
Abstract:
We analyze the dynamics of a forecasting game which exhibits the phenomenon of information cascades. Each agent aims at correctly predicting a binary variable and he/she can either look for independent information or herd on the choice of others. We show that dynamics can be analitically described in terms of a Langevin equation and its collective behavior is described by the solution of a Kramers' problem. This provides very accurate results in the region where the vast majority of agents herd, which corresponds to the most interesting one from a game theoretic point of view.
Date: 2007-05
References: Add references at CitEc
Citations:
Downloads: (external link)
http://arxiv.org/pdf/0705.4025 Latest version (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:0705.4025
Access Statistics for this paper
More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().