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Costly Information in Markets with Heterogeneous Agents: A Model with Genetic Programming

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  • Florian Hauser
  • Jürgen Huber
  • Bob Kaempff

Abstract

We analyze the value of costly information in agent-based markets with nine distinct information levels. We use genetic programming where agents optimize how much information to buy and how to process it. We find that most agents first buy high information levels, but in equilibrium buy either complete or no information, with the respective shares depending on the information costs. When information is auctioned, markets are first inefficient, so agents raise their bids to buy the highest information levels, before they learn to bid amounts that they can cover with their trading profits. In equilibrium, markets are not fully efficient, but contain just enough noise to allow informed agents to earn their information costs. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Florian Hauser & Jürgen Huber & Bob Kaempff, 2015. "Costly Information in Markets with Heterogeneous Agents: A Model with Genetic Programming," Computational Economics, Springer;Society for Computational Economics, vol. 46(2), pages 205-229, August.
    • Handle: RePEc:kap:compec:v:46:y:2015:i:2:p:205-229
    DOI: 10.1007/s10614-014-9439-6
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    References listed on IDEAS

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    Cited by:

    1. Corgnet, Brice & Deck, Cary & DeSantis, Mark & Porter, David, 2018. "Information (non)aggregation in markets with costly signal acquisition," Journal of Economic Behavior & Organization, Elsevier, vol. 154(C), pages 286-320.
    2. Wang, Zongrun & Chen, Songsheng, 2019. "Market efficiency, strategies and incomes of heterogeneously informed investors in a social network environment," Journal of Economic Behavior & Organization, Elsevier, vol. 158(C), pages 15-32.
    3. Ackert, Lucy F. & Church, Bryan K. & Zhang, Ping, 2018. "Informed traders’ performance and the information environment: Evidence from experimental asset markets," Accounting, Organizations and Society, Elsevier, vol. 70(C), pages 1-15.
    4. Lijian Wei & Xiong Xiong & Wei Zhang & Xue-Zhong He & Yongjie Zhang, 2017. "The effect of genetic algorithm learning with a classifier system in limit order markets," Published Paper Series 2017-3, Finance Discipline Group, UTS Business School, University of Technology, Sydney.

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    More about this item

    Keywords

    Agent-based simulation; Information asymmetries; Heterogeneous agents; Genetic programming; D82; D58; C61; G1;
    All these keywords.

    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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