Evolution of trading strategies in a market with heterogeneously informed agents
AbstractWe 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
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Bibliographic InfoArticle provided by Springer in its journal Journal of Evolutionary Economics.
Volume (Year): 23 (2013)
Issue (Month): 3 (July)
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Web page: http://link.springer.de/link/service/journals/00191/index.htm
Find related papers by JEL classification:
- D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
- D58 - Microeconomics - - General Equilibrium and Disequilibrium - - - Computable and Other Applied General Equilibrium Models
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
- G1 - Financial Economics - - General Financial Markets
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