Evolution of trading strategies in a market with heterogeneously informed agents

Florian Hauser () and Bob Kaempff

Journal of Evolutionary Economics, 2013, vol. 23, issue 3, 575-607

Abstract: We present an agent-based simulation of an asset market with heterogeneously informed agents. Genetic programming is applied to optimize the agents’ trading strategies. After optimization, insiders are the only agents able to generate small systematic above-average returns. For all other agents, genetic programming finds a rich variety of trading strategies that are predominantly based on exclusive subsets of their information. This limits their price impact and prevents them from making systematic losses. The resulting low noise renders market prices as largely informationally efficient. Copyright Springer-Verlag 2013

Keywords: Agent-based simulation; Heterogeneous agents; Trading strategies; Genetic programming; D82; D58; C61; G1 (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (7)

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DOI: 10.1007/s00191-011-0232-6

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