Computational modeling of collective human behavior: Example of financial markets
Abstract
We discuss how minimal financial market models can be constructed by bridging the gap between two existing, but incomplete, market models: a model in which a population of virtual traders make decisions based on common global information but lack local information from their social network, and a model in which the traders form a dynamically evolving social network but lack any decision-making based on global information. We show that a suitable combination of these two models -- in particular, a population of virtual traders with access to both global and local information -- produces results for the price return distribution which are closer to the reported stylized facts. We believe that this type of model can be applied across a wide range of systems in which collective human activity is observed.
Keywords
Cite
@article{arxiv.0812.2603,
title = {Computational modeling of collective human behavior: Example of financial markets},
author = {Andy Kirou and Blazej Ruszczycki and Markus Walser and Neil F. Johnson},
journal= {arXiv preprint arXiv:0812.2603},
year = {2008}
}
Comments
Draft of keynote lecture at International Conference on Computational Science (June, 2008). Final version published in LNCS M. Bubak et al. (Eds.) p. 33 (Springer-Verlag, Berlin, 2008)