Testing double auction as a component within a generic market model architecture
Since the first multi-agents based market simulations in the nineties, many different artificial stock market models have been developped. There are mainly used to reproduce and understand real markets statistical properties such as fat tails, volatility clustering and positive auto-correlation of absolute returns. Though they share common goals, these market models are most of the time different one from another: some are based on equations, others on complex microstructures, some are synchronous, others are asynchronous. It is hence hard to understand which characteristic of the market model used is at the origin of observed statistical properties. To investigate this question, we propose a generic model of artificial markets architecture which allows to freely compose modules coming from existing market models. To illustrate this formalism, we implement these components to propose a model of an asynchronous double auction based on an order-book and show that many stylized facts of real stock markets are reproduced with our model.
|Date of creation:||Sep 2007|
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- Gode, Dhananjay K & Sunder, Shyam, 1993. "Allocative Efficiency of Markets with Zero-Intelligence Traders: Market as a Partial Substitute for Individual Rationality," Journal of Political Economy, University of Chicago Press, vol. 101(1), pages 119-37, February.
- Cincotti, Silvano & M. Focardi, Sergio & Marchesi, Michele & Raberto, Marco, 2003. "Who wins? Study of long-run trader survival in an artificial stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 227-233.
- LeBaron, Blake & Arthur, W. Brian & Palmer, Richard, 1999.
"Time series properties of an artificial stock market,"
Journal of Economic Dynamics and Control,
Elsevier, vol. 23(9-10), pages 1487-1516, September.
- Marco Raberto & Silvano Cincott & Sergio M. Focardi & Michele Marchesi, 2002.
"Traders’ long-run wealth in an artificial financial market,"
Computing in Economics and Finance 2002
301, Society for Computational Economics.
- Marco Raberto & Silvano Cincotti & Sergio Focardi & Michele Marchesi, 2003. "Traders' Long-Run Wealth in an Artificial Financial Market," Computational Economics, Society for Computational Economics, vol. 22(2), pages 255-272, October.
- P. Bak & M. Paczuski & Martin Shubik, 1996.
"Price Variations in a Stock Market with Many Agents,"
Cowles Foundation Discussion Papers
1132, Cowles Foundation for Research in Economics, Yale University.
- Bak, P. & Paczuski, M. & Shubik, M., 1997. "Price variations in a stock market with many agents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 246(3), pages 430-453.
- P. Bak & M. Paczuski & M. Shubik, 1996. "Price Variations in a Stock Market with Many Agents," Working Papers 96-09-075, Santa Fe Institute.
- Marco Raberto & Silvano Cincotti & Sergio M. Focardi & Michele Marchesi, 2001.
"Agent-based simulation of a financial market,"
cond-mat/0103600, arXiv.org, revised Mar 2001.
- Raberto, Marco & Cincotti, Silvano & Focardi, Sergio M. & Marchesi, Michele, 2001. "Agent-based simulation of a financial market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(1), pages 319-327.
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