The effects of market structure on a heterogeneous evolving population of traders

Dan Ladley, Seth Bullock

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

1 Citation (Scopus)

Abstract

The majority of market theory is only concerned with centralised markets. In this paper, we consider a market that is distributed over a network, allowing us to characterise spatially (or temporally) separated markets. The effect of this modification on the behaviour of a market with a heterogeneous population of traders, under selection through a genetic algorithm, is examined. It is demonstrated that better-connected traders are able to make more profit than less connected traders and that this is due to a difference in the number of possible trading opportunities and not due to informational inequalities. A learning rule that had previously been demonstrated to profitably exploit network structure for a homogeneous population is shown to confer no advantage when selection is applied to a heterogeneous population of traders. It is also shown that better-connected traders adopt more aggressive market strategies in order to extract more surplus from the market.
Original languageEnglish
Title of host publicationEmergent Intelligence of Networked Agents
EditorsAkira Namatame, Satoshi Kurihara, Hideyuki Nakashima
PublisherSpringer Berlin Heidelberg
Pages83-97
Number of pages15
ISBN (Electronic)9783540710752
ISBN (Print)9783540710738
DOIs
Publication statusPublished - 2007
EventFifth International Joint Conference on Autonomous Agents and Multi-agent Systems (AAMAS 2006) - Future University, Hakodate, Japan
Duration: 8 May 200612 May 2006

Publication series

NameStudies in Computational Intelligance
PublisherSpringer Berlin Heidelberg
Volume56

Conference

ConferenceFifth International Joint Conference on Autonomous Agents and Multi-agent Systems (AAMAS 2006)
CountryJapan
CityHakodate
Period8/05/0612/05/06

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