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Computational Economics

, Volume 46, Issue 2, pp 205–229 | Cite as

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

  • Florian Hauser
  • Jürgen Huber
  • Bob Kaempff
Article

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.

Keywords

Agent-based simulation Information asymmetries  Heterogeneous agents Genetic programming 

JEL Classification

D82 D58 C61 G1 

Supplementary material

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Supplementary material 1 (gif 576 KB)
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Supplementary material 2 (gif 785 KB)

References

  1. Banzhaf, W., Nordin, P., Keller, R. E., & Francone, F. D. (1998). Genetic programming: an introduction on the automatic evolution of computer programs and its applications. San Francisco: Morgan Kaufmann Publishers Inc.Google Scholar
  2. Chen, S.-H., & Yeh, C.-H. (2001). Evolving traders and the business school with genetic programming: A new architecture of the agent-based artificial stock market. Journal of Economic Dynamics and Control, 25, 363–393.CrossRefGoogle Scholar
  3. Fama, E. F. (1970). Efficient capital markets: A review of theory and empirical work. Journal of Finance, 25(2), 383–417.CrossRefGoogle Scholar
  4. Figlewski, S. (1982). Information diversity and market behavior. Journal of Finance, 37, 87–102.CrossRefGoogle Scholar
  5. Goldbaum, D. (2006). Self-organization and the persistence of noise in financial markets. Journal of Economic Dynamics and Control, 30, 1837–1855.CrossRefGoogle Scholar
  6. Grossman, S. J. (1976). On the efficiency of competitive stock markets where traders have diverse information. Journal of Finance, 31, 573–585.CrossRefGoogle Scholar
  7. Grossman, S. J., & Stiglitz, J. E. (1980). On the impossibility of informationally efficient markets. The American Economic Review, 70, 393–408.Google Scholar
  8. Hauser, F., & Kaempff, B. (2010). Trading on marginal information. In: M. LiCalzi, L. Milone, & P. Pellizzari, (Eds.), Progress in artificial economics—computational and agent-based models lecture notes in economics and mathematical systems (Vol. 645, pp. 15–24). Berlin: Springer.Google Scholar
  9. Hauser, F., & Kaempff, B. (2011). Evolution of trading strategies in a market with heterogeneously informed agents. Journal of Evolutionary Economics, 1–33.Google Scholar
  10. Herrera, F., Lozano, M., & Verdegay, J. L. (1998). Tackling real-coded genetic algorithms: Operators and tools for the behaviour analysis. Artificial Intelligence Review, 12, 265–319.CrossRefGoogle Scholar
  11. Huber, J., Angerer, M., & Kirchler, M. (2010). Experimental asset markets with endogenous choice of costly information. Experimental Economics, 14(2), 223–240.CrossRefGoogle Scholar
  12. Hule, R., & Lawrenz, J. (2008). The value of information. some clarifications and some new results for the schredelseker-game. In M. Hanke & J. Huber (Eds.), Information, interaction and (in)efficiency in financial markets (pp. 135–155). Vienna: Linde.Google Scholar
  13. Kirman, A. (2006). Heterogeneity in economics. Journal of Economic Interaction and Coordination, 1, 89–117.CrossRefGoogle Scholar
  14. Koza, J. R. (1992). Genetic programming: On the programming of computers by means of natural selection. Cambridge, MA: The MIT Press.Google Scholar
  15. Kyle, R. A. (1985). Continuous auctions and insider trading. Econometrica, 53, 1315–1335.CrossRefGoogle Scholar
  16. LeBaron, B. (2001). A builder’s guide to agent-based financial markets. Quantitative Finance, 1, 254–261.CrossRefGoogle Scholar
  17. LeBaron, B. (2006). Agent-based computational finance. In L. Tesfatsion & K. L. Judd (Eds.), Handbook of computational economics (Vol. 2, pp. 1187–1233). Amsterdam: Elsevier.Google Scholar
  18. Lo, A. (2004). The adaptive market hypothesis: Market efficiency from an evolutionary perspective. Journal of Portfolio Management, 30, 15–29.CrossRefGoogle Scholar
  19. Michalewicz, Z. (1998). Genetic algorithms + data structures = evolution programs. New York: Springer.Google Scholar
  20. Mitchell, M. (1998). An introduction to genetic algorithms (complex adaptive systems). Cambridge, MA: MIT Press.Google Scholar
  21. Pfeifer, C., Schredelseker, K., & Seeber, G. U. H. (2009). On the negative value of information in informationally inefficient markets: Calculations for large number of traders. European Journal of Operational Research, 195, 117–126.CrossRefGoogle Scholar
  22. Schredelseker, K. (2001). Is the usefulness approach useful? Some reflections on the utility of public information. In S. McLeay & A. Riccaboni (Eds.), Contemporary issues in accounting regulation (pp. 135–153). Boston: Kluwer Academic Publishers.CrossRefGoogle Scholar
  23. Sunder, S. (1992). Market for information: Experimental evidence. Econometrica, 60(3), 667–695.CrossRefGoogle Scholar
  24. von Hayek, F. A. (1945). The use of knowledge in society. The American Economic Review, 35(4), 519–530.Google Scholar
  25. Wooldridge, M. (2009). An introduction to multiagent systems. Chichester: Wiley.Google Scholar
  26. Yeh, C.-H., & Yang, C.-Y. (2010). Examining the effectiveness of price limits in an artificial stock market. Journal of Economic Dynamics and Control, 34, 2089–2108.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Department of Banking and FinanceUniversity of InnsbruckInnsbruckAustria
  2. 2.Economics and Research DepartmentCentral Bank of LuxembourgLuxembourgLuxembourg

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