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On the convergence of genetic learning in a double auction market |
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| Authors: | Herbert Dawid |
| Affiliation: | 1. Department of Histology and Embryology, Dalian Medical University, Dalian 116044, LiaoNing Province, China;2. Department of Otorhinolaryngology of the Second Hospital, Dalian Medical University, Dalian 116023, LiaoNing Province, China;1. University of the Basque Country, School of Economics, Av. Lehendakari Aguirre 83, 48015 Bilbao, Spain;2. University of Heidelberg, Department of Economics, Bergheimer Str. 58, 69115 Heidelberg, Germany;1. Department of Finance, School of Economics, Faculty of Economics and Management, East China Normal University. 3663 North Zhongshan Rd, Shanghai 200062, China;2. Department of Economics, University at Albany, State University of New York, New York, NY 12222, USA;3. Antai College of Economics & Management, Shanghai Jiao Tong University. 1954 Huashan Rd, Shanghai 200030, China;4. Department of Industrial Economics, School of Management, Fudan University. 670 Guoshun Rd, Shanghai 200433, China |
| Abstract: | We study the learning behavior of a population of buyers and a population of sellers whose members are repeatedly randomly matched to engage in a sealed bid double auction. The agents are assumed to be boundedly rational and choose their strategies by imitating successful behavior and adding innovations triggered by random errors or communication with other agents. This process is modelled by a two-population genetic algorithm. A general characterization of the equilibria in mixed population distributions is given and it is shown analytically that only one price equilibria are attractive for the GA dynamics. Simulation results confirm these findings and imply that in cases with random initialization with high probability the gain of trade is equally split between buyers and sellers. |
| Keywords: | Double auctions Genetic algorithms Bounded rationality |
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