The value of information in a multi-agent market model

Toth, Bence and Scalas, Enrico and Huber, Juergen and Kirchler, Michael (2006): The value of information in a multi-agent market model.

Abstract

We present an experimental and simulated model of a multi-agent stock market driven by a double auction order matching mechanism. Studying the effect of cumulative information on the performance of traders, we find a non monotonic relationship of net returns of traders as a function of information levels, both in the experiments and in the simulations. Particularly, averagely informed traders perform worse than the non informed and only traders with high levels of information (insiders) are able to beat the market. The simulations and the experiments reproduce many stylized facts of stock markets, such as fast decay of autocorrelation of returns, volatility clustering and fat-tailed distribution of returns. These results have an important message for everyday life. They can give a possible explanation why, on average, professional fund managers perform worse than the market index.

• Item Type: MPRA Paper
• Language: English
• Keywords: Economics; econophysics; financial markets; business and management; information theory and communication theory
• Subjects: C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C63 - Computational Techniques ; Simulation Modeling; C - Mathematical and Quantitative Methods > C0 - General > C00 - General; G - Financial Economics > G1 - General Financial Markets > G14 - Information and Market Efficiency ; Event Studies ; Insider Trading

References

1. Cowles, A., Econometrica 1, (1933) 309-324. 2. Jensen, M., Journal of Finance 23, (1968) 389-416. 3. Malkiel, B. G., European Financial Management 9, (2003) 1-10. 4. Malkiel, B. G., Journal of Economic Perspectives 17(1), (2003) 59–82. 5. Grossman, S.J., Stiglitz, J.E., American Economic Review 70, (1980) 393-408. 6. Hellwig, M., Journal of Economic Theory 26, (1982) 279- 312. 7. Figlewski, S., Journal of Finance 37, (1982) 87-102. 8. Sunder, S., Econometrica 60, (1992) 667-695. 9. Huber, J., Kirchler, M., Sutter, M., Journal of Economic Behavior and Organization, forthcoming 10. Huber, J., Journal of Economic Dynamics and Control, forthcoming 11. Cont, R., Quantitative Finance 1, (2001) 223–236. 12. Kichler, M., Huber, J., Journal of Economic Dynamics and Control, forthcoming 13. Gibbons, J. D., Nonparametric Statistical Inference (2nd Edition, M. Dekker, 1985.) 14. Hollander, M., Wolfe, D. A., Nonpapametric Statistical Methods (Wiley, 1973.) 15. Judge, G. G., Hill, R. C., Griffiths, W. E., Lutkepohl, H., Lee, T.-C., Introduction to the Theory and Practice of Econometrics (New York, Wiley, 1988.) 16. LiCalzi, M., Pellizzari, P., Quantitative Finance 3, (2003) 1–11.