Evolution of trading strategies in a market with heterogeneously informed agents

被引：0
|
作者：
Florian Hauser
Bob Kaempff
机构：
[1] Innsbruck University School of Management,Department of Banking and Finance
来源：
Journal of Evolutionary Economics | 2013年 / 23卷
关键词：
Agent-based simulation; Heterogeneous agents; Trading strategies; Genetic programming; D82; D58; C61; G1;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
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.
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页码：575 / 607
页数：32
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