Evolving Traders and the Faculty of the Business School: A New Architecture of the Artificial Stock Market
In this paper, we propose a new architecture to study artificial stock markets. This architecture rests on a mechanism called "school" which is a procedure for mapping the phenotype to the genotype or, in plain English, to uncover the secret of success. We propose an agent-based model of school, considering it as an evolving population driven by single-population GP (SGP). The architecture also takes into consideration traders' search behaviour. By simulated annealing, the traders' search densities can be connected to psychological factors such as peer pressure or to economic factors such as the standard of living. This market architecture is then implemented in a standard artificial stock market. Our econometric study of the resultant artificial time series gives evidence that the return series is independently and identically distributed (iid) and hence supports the efficient market hypothesis (EMH). What is interesting, though, is that this iid series is generated by traders who do not believe in the EMH at all. In fact, our study indicates that many of our traders are often able to find useful signals from business school, even though these signals are short-lived.
|Date of creation:||01 Mar 1999|
|Date of revision:|
|Contact details of provider:|| Postal: CEF99, Boston College, Department of Economics, Chestnut Hill MA 02467 USA|
Web page: http://fmwww.bc.edu/CEF99/
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Robert Axelrod, 1997. "Advancing the Art of Simulation in the Social Sciences," Working Papers 97-05-048, Santa Fe Institute.
- Lux, T. & M. Marchesi, . "Scaling and Criticality in a Stochastic Multi-Agent Model of a Financial Market," Discussion Paper Serie B 438, University of Bonn, Germany, revised Jul 1998.
- D. Heymann, R. P. J. Perazzo, & Andres Schuschny, . "Learning and Contagion Effects in Trasitions Between Regimes: A Schematic Model of Bank Runs," Computing in Economics and Finance 1997 17, Society for Computational Economics.
- Pagan, Adrian, 1996. "The econometrics of financial markets," Journal of Empirical Finance, Elsevier, vol. 3(1), pages 15-102, May.
- Tony Curzon Price, 1997. "Using co-evolutionary programming to simulate strategic behaviour in markets," Journal of Evolutionary Economics, Springer, vol. 7(3), pages 219-254.
- Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-72, June.
- Arifovic, Jasmina, 1994. "Genetic algorithm learning and the cobweb model," Journal of Economic Dynamics and Control, Elsevier, vol. 18(1), pages 3-28, January.
- James Bullard & John Duffy, 2010.
"Using genetic algorithms to model the evolution of heterogenous beliefs,"
Levine's Working Paper Archive
550, David K. Levine.
- Bullard, James & Duffy, John, 1999. "Using Genetic Algorithms to Model the Evolution of Heterogeneous Beliefs," Computational Economics, Society for Computational Economics, vol. 13(1), pages 41-60, February.
- James B. Bullard & John Duffy, 1994. "Using genetic algorithms to model the evolution of heterogeneous beliefs," Working Papers 1994-028, Federal Reserve Bank of St. Louis.
- James B. Bullard & John Duffy, 1995. "On learning and the stability of cycles," Working Papers 1995-006, Federal Reserve Bank of St. Louis.
- Bullard, James & Duffy, John, 1998. "Learning And The Stability Of Cycles," Macroeconomic Dynamics, Cambridge University Press, vol. 2(01), pages 22-48, March.
- Shu-Heng Chen & Thomas Lux & Michele Marchesi, 1999.
"Testing for Non-Linear Structure in an Artificial Financial Market,"
Discussion Paper Serie B
447, University of Bonn, Germany.
- Chen, Shu-Heng & Lux, Thomas & Marchesi, Michele, 2001. "Testing for non-linear structure in an artificial financial market," Journal of Economic Behavior & Organization, Elsevier, vol. 46(3), pages 327-342, November.
- Lux, Thomas, 1998. "The socio-economic dynamics of speculative markets: interacting agents, chaos, and the fat tails of return distributions," Journal of Economic Behavior & Organization, Elsevier, vol. 33(2), pages 143-165, January.
- Arifovic, Jasmina & Bullard, James & Duffy, John, 1997. "The Transition from Stagnation to Growth: An Adaptive Learning Approach," Journal of Economic Growth, Springer, vol. 2(2), pages 185-209, July.
- Holland, John H & Miller, John H, 1991. "Artificial Adaptive Agents in Economic Theory," American Economic Review, American Economic Association, vol. 81(2), pages 365-71, May.
- Arifovic, Jasmina, 1996. "The Behavior of the Exchange Rate in the Genetic Algorithm and Experimental Economies," Journal of Political Economy, University of Chicago Press, vol. 104(3), pages 510-41, June.
- repec:cup:macdyn:v:2:y:1998:i:1:p:22-48 is not listed on IDEAS
- Arifovic, Jasmina, 1995. "Genetic algorithms and inflationary economies," Journal of Monetary Economics, Elsevier, vol. 36(1), pages 219-243, August.
- James B. Bullard & John Duffy, 1994.
"A model of learning and emulation with artificial adaptive agents,"
1994-014, Federal Reserve Bank of St. Louis.
- Bullard, James & Duffy, John, 1998. "A model of learning and emulation with artificial adaptive agents," Journal of Economic Dynamics and Control, Elsevier, vol. 22(2), pages 179-207, February.
- Lux, Thomas, 1995. "Herd Behaviour, Bubbles and Crashes," Economic Journal, Royal Economic Society, vol. 105(431), pages 881-96, July.
- W. Brian Arthur & John H. Holland & Blake LeBaron & Richard Palmer & Paul Taylor, 1996.
"Asset Pricing Under Endogenous Expectation in an Artificial Stock Market,"
96-12-093, Santa Fe Institute.
- Arthur, W.B. & Holland, J.H. & LeBaron, B. & Palmer, R. & Tayler, P., 1996. "Asset Pricing Under Endogenous Expectations in an Artificial Stock Market," Working papers 9625, Wisconsin Madison - Social Systems.
- Vriend, Nicolaas J., 2000. "An illustration of the essential difference between individual and social learning, and its consequences for computational analyses," Journal of Economic Dynamics and Control, Elsevier, vol. 24(1), pages 1-19, January.
- Miller, John H., 1996. "The coevolution of automata in the repeated Prisoner's Dilemma," Journal of Economic Behavior & Organization, Elsevier, vol. 29(1), pages 87-112, January.
When requesting a correction, please mention this item's handle: RePEc:sce:scecf9:613. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum)
If references are entirely missing, you can add them using this form.