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Convergence of outcomes and evolution of strategic behavior in double auctions

Shira Fano (), Marco Li Calzi () and Paolo Pellizzari
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Marco Li Calzi: Dept. of Applied Mathematics and Advanced School of Economics, University of Venice

Authors registered in the RePEc Author Service: Marco Li Calzi

No 196, Working Papers from Department of Applied Mathematics, Università Ca' Foscari Venezia

Abstract: We study the emergence of strategic behavior in double auctions with an equal number n of buyers and sellers, under the distinct assumptions that orders are cleared simultaneously or asynchronously. The evolution of strategic behavior is modeled as a learning process driven by a genetic algorithm. We find that, as the size n of the market grows, allocative inefficiency tends to zero and performance converges to the competitive outcome, regardless of the order-clearing rule. The main result concerns the evolution of strategic behavior. Under simultaneous order-clearing, as n increases, only marginal traders learn to be price takers and make offers equal to their valuations/costs. Under asynchronous order-clearing, as n increases, all intramarginal traders learn to be price makers and make offers equal to the competitive equilibrium price. The nature of the order-clearing rule affects in a fundamental way what kind of strategic behavior we should expect to emerge.

Keywords: Trading protocols; asymptotic equivalence; learning; genetic algorithms. (search for similar items in EconPapers)
JEL-codes: C63 C72 D44 D82 (search for similar items in EconPapers)
Pages: 27 pages
Date: 2010-02
New Economics Papers: this item is included in nep-cmp
References: View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Forthcoming in Journal of Evolutionary Economics

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Related works:
Journal Article: Convergence of outcomes and evolution of strategic behavior in double auctions (2013) Downloads
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