Skip to main content

Multi-Agent Simulation of Financial Markets

  • Chapter

Part of the book series: International Handbooks on Information Systems ((INFOSYS))

Abstract

This paper discusses the principal reasons for, and prospective opportunities of, simulating financial markets using an architecture based on artificial agents. The paper then discusses in detail the design and architecture of a simulator for financial markets. The Gaia methodology was employed in the development of MAFiMSi (Multi-Agent Finanacial Market Simulator), a general-purpose finacial market simulator of a dealer-type market. MAFiMSi is implemented as a library of C++ classes that currently support a stand-alone market simulation.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [AHL+97]_W. B. Arthur, J. H. Holland, Blake LeBaron, R. G. Palmer, and P. Tayler, Asset pricing under endogenous expectations in an artificial stock market, The Economy as an Evolving Complex System II (Menlo Park, CA) (W. B. Arthur, D. Lane, and S. N. Durlauf, eds.), Adisson-Wesley, 1997.

    Google Scholar 

  2. Christopher H. Brooks, Edmund H. Durfee, and Rajarshi Das, Price wars and niche discovery in an information economy, Proceedings of ACM Conference on Electronic Commerce (EC-00) (Minneapolis, MN), October 2000.

    Google Scholar 

  3. Sergio Focardi and Caroline Jonas, Modeling the market: New theories and techniques, Frank J. Fabozzi Associates, New Hope, Pennsylvania, 1997.

    Google Scholar 

  4. Ming Fan, Jan Stallaert, and Andrew B. Whinston, The internet and the future of financial markets, Communications of the ACM 43 (2000), no. 11, 82–88.

    Article  ISI  Google Scholar 

  5. J. Michael Harrison and Stanley R. Pliska, Martingales and stochastic integrals in the theory of continuous time trading, Stochastic Processes and their Applications 11 (1981), 215–260.

    Article  MathSciNet  Google Scholar 

  6. Tamer M. Őzsu and P. Valduriez, Principles of distributed database systems, Prentice Hall, Upper Saddle River, New Jersey, 1999.

    Google Scholar 

  7. IBM, IBM Optimization Solutions and Library, 2004, http://www3.ibm.com/software/data/bi/osl/index.html.

    Google Scholar 

  8. Kiyoshi Izumi and Kazuhiro Ueda, Analysis of dealers’ processing financial news based on an artificial market approach, Journal of Computational Intelligence in Finance 7 (1999), 23–33.

    Google Scholar 

  9. —, Analysis of exchange rate scenarios using an artificial market approach, Proceedings of the International Conference on Artificial Intelligence (A. Amin, C.-H. Chen, and et. al, eds.), CSREA Press, 1999, pp. 360–366.

    Google Scholar 

  10. S. Joshi, J. Parker, and M. A. Bedau, Technical trading creates prisoner’s dilemma: Results from an agent-based model, Computational Finance (Cambidge, MA) (Y. S. Abu-Mostafa, Blake LeBaron, A. W. Lo, and A. S. Weigend, eds.), The MIT Press, 1999.

    Google Scholar 

  11. Jeffry O. Kephart, James E. Hansen, and Amy R. Greenwald, Dynamic pricing by software agents, Computer Networks 32 (2000), no. 6, 731–752.

    Article  ISI  Google Scholar 

  12. [KHL+98a]_Jeffrey O. Kephart, James E. Hanson, David W. Levine, Benjamin N. Grosof, Jakka Sairamesh, Richard B. Segaland, and Steve R. White, Dynamics of an information-filtering economy, Proceedings of the Second International Workshop on Cooperative Information Agents, July 1998.

    Google Scholar 

  13. [KHL+98b]_Jeffry O. Kephart, James E. Hansen, D. W. Levine, Benjamin Grosof, J. Sairamesh, R. Segal, and S. R. White, Emergent behavior in information economies, Proceedings of the International Conference on Multi-Agent Systems, 1998.

    Google Scholar 

  14. Ioanis Karatzas and Steven Shreve, Methods of mathematical finance, Springer-Verlag, new York, New York, 1998.

    Google Scholar 

  15. Blake LeBaron, W. B. Arthur, and R. G. Palmer, The time series properties of an artificial stock market, Journal of Economic Dynamics and Control 23 (1999), 1487–1516.

    Article  Google Scholar 

  16. Blake LeBaron, Agent-based computational finanace: Suggested readings and early research, Journal of Economic Dynamics and Control 24 (2000), 679–702.

    Article  MATH  Google Scholar 

  17. —, A builder’s guide to agent-based financial markets, Quantitative Finance 1 (2001), 254–261.

    Article  Google Scholar 

  18. —, Evolution and time horizons in an agent based stock market, Macroeconomic Dynamics 5 (2001), 254–261.

    Article  MATH  Google Scholar 

  19. P. Maes, R. Guttman, and A. Moukas, Agents that buy and sell, Communications of tha ACM 42 (1999), no. 3, 81–91.

    Article  Google Scholar 

  20. R. G. Palmer, W. B. Arthur, J. H. Holland, and Blake LeBaron, Artificial economic life: a simple model of a stock market, Physica D 75 (1994), 264–274.

    Article  ADS  ISI  Google Scholar 

  21. Frank Partnoy, Fiasco the inside story of a wall street trader, Penguin Books, New York, 1997.

    Google Scholar 

  22. Arnold Picot, Christine Bortenlänger, and Heine Röhrl, The automation of capital markets, Journal of Computer-Mediated Commerce 1 (1995), no. 3. Available online at http://www.ascusc.org/jcmc/-vol1/issue3/picot.html.

    Google Scholar 

  23. S. Russell and P. Norvig, Artificial intelligence, Prentice Hall, New Jersey, 1995.

    Google Scholar 

  24. John Rust, Dealing with the complexity of economic calculations, 1996, Workshop on Foundamental Limits to Knowledge in Economics.

    Google Scholar 

  25. Tuomas Sandholm, eMediator: A next generation electronic commerce server, AAAI Workshop Technical Report WS-99-01 (Orlando, Fl), AAAI Workshop on AI in Electronic Commerce, 1999, pp. 46–55.

    Google Scholar 

  26. Securities and Exchange Commission, Securities and Exchange Commission special study: On-line brokerage: Keeping apace of cyberspace, November 1999, Available online at http://www.sec.gov/news/studies/cyberspace.htm.

    Google Scholar 

  27. Olga Streltchenko, Nanjangud C. Narendra, and Yelena Yesha, A reference architecture for multi-agent simulation of derivatives markets, Proceedings of the International ICSC Congress on Computational Intelligence: Methods and Applications (Bangor, Wales), 2001.

    Google Scholar 

  28. Leigh Tesfatsion, Notes on the Santa Fe Artificial Stock Market model, Available online at http://www.econ.iastate.edu/classes/econ308x/tesfatsion/sfistock.htm, 2002.

    Google Scholar 

  29. Gerald J. Tesauro and Jeffrey O. Kephar, Foresight-based pricing algorithms in an economy of software agents, Proceedings of International Conference on Information and Computation Economies, October 1998.

    Google Scholar 

  30. Hal Varian, Effect of the internet on financial markets, 1998, Available online at http://www.sims.berkeley.edu/∼hal/Papers/brookingspaper. html.

    Google Scholar 

  31. Michael Wooldridge, Nicholas Jennings, and D. Kinny, The gaia methodology for agent-oriented analysis and design, Journal of Autonomous Agents and Multi-Agent Systems 3 (2000), no. 3, 285–312.

    Article  Google Scholar 

  32. Frank G. Zarb, The coming global digital stock market, speech at the National Press Club, 1999, Available online at http://www.nasdaqnews.com/views/speech/digmarkets.htm.

    Google Scholar 

  33. Franco Zambonelly, Nicholas Jennings, and Michael Wooldridge, Organizational abstractions for the analysis and design of multi-agent systems, Proceedings of the Firstst International Workshop on Agent-Oriented Software Engineering (Limerick, Ireland), 2000, pp. 127–141.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Streltchenko, O., Yesha, Y., Finin, T. (2005). Multi-Agent Simulation of Financial Markets. In: Kimbrough, S.O., Wu, D. (eds) Formal Modelling in Electronic Commerce. International Handbooks on Information Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-26989-4_15

Download citation

Publish with us

Policies and ethics