The effects of market structure on a heterogeneous evolving population of traders
The effects of market structure on a heterogeneous evolving population of traders
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.
83-97
Ladley, Dan
eadd9d0e-cba3-48d3-9e4d-61fe9a5ab1bd
Bullock, Seth
2ad576e4-56b8-4f31-84e0-51bd0b7a1cd3
3 May 2007
Ladley, Dan
eadd9d0e-cba3-48d3-9e4d-61fe9a5ab1bd
Bullock, Seth
2ad576e4-56b8-4f31-84e0-51bd0b7a1cd3
Ladley, Dan and Bullock, Seth
(2007)
The effects of market structure on a heterogeneous evolving population of traders.
Namatame, Akira, Kurihara, Satoshi and Nakashima, Hideyuki
(eds.)
In Emergent Intelligence of Networked Agents.
vol. 56,
Springer Berlin.
.
(doi:10.1007/978-3-540-71075-2_7).
Record type:
Conference or Workshop Item
(Paper)
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.
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e-pub ahead of print date: 25 April 2007
Published date: 3 May 2007
Venue - Dates:
Agent-Mediated Electronic Commerce: Designing Trading Agents and Mechnisms, Edinburgh, United Kingdom, 2005-07-30 - 2005-08-05
Organisations:
Agents, Interactions & Complexity
Identifiers
Local EPrints ID: 263461
URI: http://eprints.soton.ac.uk/id/eprint/263461
ISSN: 1860-949X
PURE UUID: dceb1c51-a342-4b99-b4bc-60027b5d019b
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Date deposited: 15 Feb 2007
Last modified: 14 Mar 2024 07:32
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Contributors
Author:
Dan Ladley
Editor:
Akira Namatame
Editor:
Satoshi Kurihara
Editor:
Hideyuki Nakashima
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