TY - GEN
T1 - The effects of market structure on a heterogeneous evolving population of traders
AU - Ladley, Dan
AU - Bullock, Seth
PY - 2007
Y1 - 2007
N2 - 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.
AB - 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.
UR - http://seis.bris.ac.uk/~sb15704/pubs_abstracts.html#eps263462
U2 - 10.1007/978-3-540-71075-2_7
DO - 10.1007/978-3-540-71075-2_7
M3 - Conference Contribution (Conference Proceeding)
SN - 9783540710738
T3 - Studies in Computational Intelligance
SP - 83
EP - 97
BT - Emergent Intelligence of Networked Agents
A2 - Namatame, Akira
A2 - Kurihara, Satoshi
A2 - Nakashima, Hideyuki
PB - Springer Berlin Heidelberg
T2 - Fifth International Joint Conference on Autonomous Agents and Multi-agent Systems (AAMAS 2006)
Y2 - 8 May 2006 through 12 May 2006
ER -