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

Volumn 25, Issue 3-4, 2001, Pages 363-393

  Chen, Shu Heng ^a   Yeh, Chia Hsuan ^b  

^a NATIONAL CHENGCHI UNIVERSITY   (Taiwan)

^b I SHOU UNIVERSITY   (Taiwan)

Author keywords

Agent based computational economics; Artificial stock markets; Business school; D83; G12; G14; Genetic programming; Social learning

Indexed keywords

EID: 0006162009     PISSN: 01651889     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0165-1889(00)00030-0     Document Type: Article

References (39)

1. Andrews M., Prager R. Genetic programming for the acquisition of double auction market strategies. Kinnear K.E. Advances in Genetic Programming, Vol. 1. 1994;355-368 MIT Press, Cambridge.
2. Arifovic J. Genetic algorithm learning and the cobweb model. Journal of Economic Dynamics and Control. 18(1):1994;3-28.
3. Arifovic J. Genetic algorithms and inflationary economies. Journal of Monetary Economics. 36:1995;219-243.
4. Arifovic J. The behavior of the exchange rate in the genetic algorithm and experimental economies. Journal of Political Economy. 104(3):1996;510-541.
5. Arifovic J., Bullard J., Duffy J. The transition from stagnation to growth: an adaptive learning approach. Journal of Economic Growth. 2:1997;185-209.
6. Arthur W.B., Holland J., LeBaron B., Palmer R., Tayler P. Asset pricing under endogenous expectations in an artificial stock market. Arthur W.B., Durlauf S., Lane D. The Economy as an Evolving Complex System II. 1997;15-44 Addison-Wesley, Reading, MA.
7. Bullard J., Duffy J. A model of learning and emulation with artificial adaptive agents. Journal of Economic Dynamics and Control. 22:1998;179-207.
8. Bullard J., Duffy J. Learning and the stability of cycles. Macroeconomic Dynamics. 2:1998;22-48.
9. Bullard, J., Duffy, J., 1999. Using genetic algorithms to model the evolution of heterogeneous beliefs. Computational economics 13, 41-60.
10. Chen, S.-H., Yeh, C.-H., 1996. Genetic Programming Learning and the Cobweb Model, Advances in Genetic Programming, Vol. 2. MIT Press, Cambridge, MA, 1996, pp. 443-466. (Chapter 22).
11. Chen, S.-H., Yeh, C.-H., 1997. Modeling speculators with genetic programming. In: Angeline, P., Reynolds, R.G., McDonnell, J.R., Eberhart, R. (Eds.), Evolutionary Programming VI. Lecture Notes in Computer Science, Vol. 1213. Springer, Berlin, pp. 137-147.
12. Chen, S.-H., Yeh, C.-H., 1998. Genetic programming in the overlapping generations model: an illustration with dynamics of the inflation rate. In: Porto, V.W., Saravanan, N., Waagen, D., Eiben, A.E. (Eds.), Evolutionary Programming VII. Lecture Notes in Computer Science, Vol. 1447. Springer, Berlin, pp. 829-838.
13. Chen, S.-H., Kuo, T.-W., 1999. Towards an agent-based foundation of financial econometrics: an approach based on genetic-programming artificial markets, In: Banzhaf, W., Daida, J., Eiben, A.E., Garzon, M.H., Honavar, V., Jakiela, M., Smith, R.E. (Eds.), GECCO-99: Proceedings of the Genetic and Evolutionary Computation Conference, July 13-17, 1999, Orlando, FL, USA, Vol. 2. Morgan Kaufmann, San Francisco, CA, pp. 966-973.
14. Chen, S.-H., Yeh, C.-H., 2000. Issues in the sensitivity analysis of agent-based modeling of artificial stock markets. AI-ECON Research Group Working Paper 2000-1, Department of Economics, National Chengchi University, Taipei, Taiwan.
15. Chen S.-H., Duffy J., Yeh C.-H. Genetic programming in the coordination game with a chaotic best-response function. Angeline P., Back T., Fogel D. Evolutionary Programming V. 1996;277-286 MIT Press, Cambridge, MA.
16. Chen, S.-H., Liao, C.-C., Yeh, C.-H., 2000a. On AIE-ASM: a software to simulate artificial stock markets with genetic programming. In: Chen, S.-H. (Ed.), Evolutionary Computation in Economics and Finance. Physica-Verlag, Wurzburg, forthcoming.
17. Chen, S.-H., Lux, T., Marchesi, M., 2000b. Testing for non-linear structure in an artificial financial market. Journal of Economic Behavior and Organization, forthcoming.
18. Dickey D.A., Fuller W.A. Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica. 49:1981;1057-1072.
19. Grossman S.J., Stiglitz J. On the impossibility of informationally efficiency markets. American Economic Review. 70:1980;393-408.
20. Harrald, P., 1998. Economics and evolution. The panel paper given at the Seventh International Conference on Evolutionary Programming, March 25-27, San Diego, U.S.A.
21. Herreiner, D., 1998. Who learns from what from whom? Paper presented at the Fourth International Conference of the Society for Computational Economics, June 30-July 2, Cambridge, U.K.
22. Heymann D., Pearzzo R.P.J., Schuschny A. Learning and contagion effects in transitions between regimes: some schematic multi-agents models. Journal of Management and Economics. 2(6):1998.
23. Holland J.H., Miller J.H. Artificial Adaptive Agents in Economic Theory, American Economic Review (Papers and Proceedings). 81(2):1991;365-370.
24. Koza, J., 1992. Genetic Programming: On the Programming of Computers by means of natural selection, MIT.
25. LeBaron, B., 2000. Agent-based computational finance: suggested readings and early research. Journal of Economic Dynamics and Control 24, 679-702.
26. Lux T. Herd behavior, bubbles and crashes. Economic Journal. 105:1995;881-896.
27. Lux T. The socio-economic dynamics of speculative markets: interacting agents, chaos, and the fat tails of return distribution. Journal of Economic Behavior and Organization. 33:1998;143-165.
28. Lux, T., Marchesi, M., 1999. Scaling and criticality in a stochastic multi-agent model of a financial market, Nature, 397, S. 498-500.
29. Miller J.H. The coevolution of automata in the repeated prisoner's dilemma. Journal of Economic Behavior and Organization. 29:1996;87-112.
30. Minsky M.L. The Society of Mind. 1986;Simon & Schuster, New York.
31. Pagan A. The econometrics of financial markets. Journal of Empirical Finance. 3:1996;15-102.
32. Palmer R.G., Arthur W.B., Holland J.H., LeBaron B., Tayler P. Artificial economic life: a simple model of a stock market. Physica D. 75:1994;264-274.
33. Peters, E.E., 1991. A chaotic attractor for the S&P 500. Financial Analysts Journal, March/April.
34. Price T.C. Using co-evolutionary programming to simulate strategic behavior in markets. Journal of Evolutionary Economics. 7:1997;219-254.
35. Sargent, T.J., 1993. Bounded Rationality in Macroeconomics. Oxford.
36. Staudinger, S., 1998. Money as medium of exchange: an analysis with genetic algorithms. In: Proceedings of Conference on Computation in Economics, Finance, and Engineering, June 29-July 1, University of Cambridge.
37. Tayler, P., 1995. Modeling artificial stock markets using genetic algorithms. In: Goonatilake, S., Treleaven, P. (Eds.), Intelligent Systems for Finance and Business, pp. 271-288.
38. Vila, X., 1997. Adaptive artificial agents play a finitely repeated discrete principal-agent game. In: Conte, R., Hegselmann, R., Terna, P. (Eds.), Simulating Social Phenomena. Lecture Notes in Economics and Mathematical Systems, Springer, Berlin, pp. 437-456.
39. Vriend, N., 1998. An illustration of the essential difference between individual and social learning, and its consequence for computational analysis. Technical Report, Queen Mary and Westfield College, University of London, U.K.