Skip to main content
SpringerLink
Log in

Critical Review of Agent-Based Models

  • Chapter
  • First Online:
Complexity in Financial Markets

Part of the book series: Springer Theses ((Springer Theses))

Abstract

In this chapter we present a critical discussion of some of the most representative Agent-Based Models (ABM hereafter) of Economics. We embed them in a framework which highlights their key principles and the relative strengths and weaknesses. The objective is to point out the possible lines of convergency and improvement in order to focus towards an optimal model. A crucial weakness in this respect is that the experimental framework defined by the so-called Stylized Facts is still rather limited and an improvement of this body of knowledge appears to be the bottle neck in the field.

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

Access this chapter

Log in via an institution
eBook
USD 16.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
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

Institutional subscriptions

References

  1. Buchanan, M. (2008). Why economic theory is out of whack. New Scientist, 2665, 32.

    Article  Google Scholar 

  2. Kreps, D. M. (1990). A course in microeconomic theory. Princeton: Princeton University Press.

    Google Scholar 

  3. Bachelier, L. (1900). Théorie de la spéculation. Annales Scientifiques de l’Ecole Normale Supérieure III-17, 21. (Ph.D. thesis is mathematics).

    Google Scholar 

  4. Feller, W. (1968). An introduction to probabbility and its applications (Vol. 1). New York: Wiley.

    Google Scholar 

  5. Black, F., & Scholes, M. (1973). The pricing of options and corporate liabilities. Journal of Political Economy, 81, 637.

    Article  Google Scholar 

  6. Hull, J. C. (1997). Options features and other derivatives. Upper Saddle River NJ: Prentice-Hall.

    Google Scholar 

  7. Cutler, D. M., Poterba, J. M., & Summers, L. H. (1989). What moves stock prices? The Journal of Portfolio Management, 15, 4.

    Article  Google Scholar 

  8. Pietronero, L. (2008). Complexity ideas from condensed matter and statistical physics. Europhysics News, 39, 26.

    Article  ADS  Google Scholar 

  9. Bouchaud, J.-P. (2008). Economics needs a scientific revolution. Nature, 455, 1181.

    Article  ADS  Google Scholar 

  10. Farmer, J. D., & Foley, D. (2009). The economy needs agent-based modelling. Nature, 460, 685.

    Article  ADS  Google Scholar 

  11. Arrow, J. K., & Debreu, G. (1954). Existence of an equilibrium for a competitive economy. Econometrica, 22, 265.

    Article  MathSciNet  MATH  Google Scholar 

  12. Debreu, G. (1959). Theory of value. New York: Wiley.

    Google Scholar 

  13. Arrow, J. K. (1953). Le role des valeurs boursieres pour la repartition la meilleure des risques. Econometrie, 11, 41.

    Google Scholar 

  14. Arthur, W., Holland, J. H., LeBaron, B., Palmer, R., & Tyler, P. (1996). Asset pricing under endogenous expectation in an artificial stock market. Retrieved from http://www2.econ.iastate.edu/tesfatsi/ahlpt96.pdf.

  15. Chakraborti, A., Toke, I. M., Patriarca, M., & Abergel, F. (2011) Econophysics: Empirical facts and agent-based models. Quantitative Finance (in press). Retrieved from http://arxiv.org/abs/arXiv:0909.1974v2.

  16. Samanidou, E., Zschischang, E., Stauffer, D., & Lux, T. (2007). Microscopic models of financial markets. Reports on Progress in Physics, 70, 409–450.

    Google Scholar 

  17. Hommes, C. H. (2005). Heterogeneous agent models in economics and finance. Tinbergen Institute Discussion Papers 05–056/1, Tinbergen Institute. Retrieved from: http://ideas.repec.org/p/dgr/uvatin/20050056.html.

  18. Report of the presidential task force on market mechanisms. (1988). Tech. The Brady Commission, Washington DC : Rep. US Government Commission Printing Office.

    Google Scholar 

  19. Schwert, G. W. (1990). Stock volatility and the crash of 87. Review of Financial Studies, 3, 77.

    Article  Google Scholar 

  20. Kim, G., & Markowitz, H. M. (1989). Investment rules, margin and market volatility. Journal of Portfolio Management, 16, 45.

    Article  Google Scholar 

  21. Brennan, M. J., & Schwartz, E. S. (1989). Portfolio insurance and financial market equilibrium. Journal of Business, 62, 455.

    Google Scholar 

  22. Palmer, R., Arthur, W., Holland, J. H., LeBaron, B., & Tyler, P. (1994). Artificial economic life: a simple model of a stockmarket. Physica D, 75, 264.

    Google Scholar 

  23. Roehner, B. M. (2002). Patterns of speculation. Cambridge: Cambridge Univeristy Press.

    Google Scholar 

  24. Challet, D., Marsili, M., & Zhang, Y.-C. (2005). Minority games: Interacting agents in financial markets. New York, NY, USA: Oxford University Press, Inc.

    Google Scholar 

  25. De Martino, A. (2006). Statistical mechanics of socio-economic systems with heterogeneous agents. Journal of Physics A: Mathematical and General, 39, R465.

    Article  MATH  Google Scholar 

  26. Arthur, B. W. (1994). Inductive reasoning and bounded rationality: The el farol problem. American Economic Review, 84, 406.

    Google Scholar 

  27. Challet, D., & Zhang, Y. (1997). Emergence of cooperation and organization in an evolutionary game. Physica A, 246, 407.

    Article  ADS  Google Scholar 

  28. Challet, D., Marsili, M., & Zhang, Y.-C. (2001). Stylized facts of financial markets and market crashes in minority games. Physica A: Statistical Mechanics and its Applications, 294(3), 514–524.

    Google Scholar 

  29. Challet, D., & Marsili, M. (2003). Criticality and market efficiency in a simple realistic model of the stock market. Physical Review E, 68, 036132.

    Article  ADS  Google Scholar 

  30. Challet, D., Marsili, M., & Zecchina, R. (2000). Statistical mechanics of systems with heterogeneous agents: Minority games. Physical Review Letters, 84, 1824.

    Article  ADS  Google Scholar 

  31. Mezard, M., Parisi, G., & Virasoro, M. (1986). Spin glass theory and beyond: an introduction to the replica method and its applications (World Scientific Lecture Notes in Physics).

    Google Scholar 

  32. Caldarelli, G., Marsili, M., & Zhang, Y.-C. (1997). A prototype model of stock exchange. Europhysics Letters, 40, 479.

    Article  ADS  Google Scholar 

  33. Golke, S., Preis, T., Paul, W., & Schneider, J. J. Comment on a prototype model of stock exchange by G. Caldarelli, M. Marsili, and Y.-C. Zhang. Retrieved from http://www.staff.uni-mainz.de/schneidj/papers/papergolke.pdf.

  34. Lux, T., & Marchesi, M. (1999). Scaling and criticality in a stochastic multi-agent model of a financial market. Nature, 397, 498.

    Article  ADS  Google Scholar 

  35. Lux, T., & Marchesi, M. (2000). Volatility clustering in financial markets: A micro-simulation of interacting agents. International Journal of Theoretical and Applied Finance, 3, 675.

    Article  MathSciNet  MATH  Google Scholar 

  36. Kirman, A. (1993). Ants, rationality and recruitment. The Quarterly Journal of Economics, 108, 137.

    Article  Google Scholar 

  37. Alfarano, S., Lux, T., & Wagner, F. (2005). Estimation of agent-based models: the case of an asymmetric herding model. Computational Economics, 26, 19.

    Article  MATH  Google Scholar 

  38. Alfi, V., Cristelli, M., Pietronero, L., & Zaccaria, A. (2009). Minimal agent based model for financial markets I: origin and self-organization of stylized facts. European Physical Journal B, 67, 385. http://arxiv.org/abs/0808.3562.

  39. Egenter, E., Lux, T., & Stauffer, D. (1999). Finite-size effects in monte carlo simulations of two stock market models. Physica A, 268, 250.

    Article  Google Scholar 

  40. Alfi, V., Pietronero, L., & Zaccaria, A. (2009). Self-organization for the stylized facts and finite-size effects in a financial-market model. EPL, 86, 58003.

    Google Scholar 

  41. Alfi, V., Cristelli, M., Pietronero, L., & Zaccaria, A. (2009). Minimal agent based model for financial markets II: statistical properties of the linear and multiplicative dynamics. European Physical Journal B, 67, 399. http://arxiv.org/abs/0808.3565.

  42. Giardina, I., & Bouchaud, J.-P. (2003). Bubbles, crashes and intemittency in agent based market. European Physical Journal B, 31, 421.

    Article  MathSciNet  ADS  Google Scholar 

  43. Bouchaud, J.-P., Giardina, I., & Mézard, M. (2001). On a universal mechanism for long ranged volatility correlations. Quantitative Finance, 1, 212.

    Google Scholar 

  44. Alfi, V., Cristelli, M., Pietronero, L., & Zaccaria, A. (2009). Mechanisms of self-organization and finite size effects in a minimal agent based model. Journal of Statistical Mechanics, P03016. doi:10.1088/1742-5468/2009/03/P03016

Download references

Author information

Authors and Affiliations

  1. ISC-CNR, Istituto dei Sistemi Complessi, Department of Physics, ”Sapienza”, Università di Roma, Piazzale Aldo Moro 5, 00185, Rome, Italy

    Matthieu Cristelli

Authors
  1. Matthieu Cristelli
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Matthieu Cristelli .

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Cristelli, M. (2014). Critical Review of Agent-Based Models. In: Complexity in Financial Markets. Springer Theses. Springer, Cham. https://doi.org/10.1007/978-3-319-00723-6_3

Download citation

Publish with us

Policies and ethics

Search

Navigation