Computational modeling of collective human behavior: Example of financial markets

Simple item page
dc.creatorKirou, Andy
dc.creatorRuszczycki, Blazej
dc.creatorWalser, Markus
dc.creatorJohnson, Neil F.
dc.date2008-12-14
dc.date.accessioned2026-07-07T12:12:45Z
dc.date.available2026-07-07T12:12:45Z
dc.descriptionWe 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.
dc.descriptionDraft 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)
dc.identifierhttps://arxiv.org/abs/0812.2603
dc.identifierhttp://arxiv.org/abs/0812.2603
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/210648
dc.subjectTrading and Market Microstructure
dc.subjectComputational Physics
dc.titleComputational modeling of collective human behavior: Example of financial markets
dc.typetext

Files

Collections

arXiv