Multi-agent modeling and simulation of a stock market
-
DOIhttp://dx.doi.org/10.21511/imfi.15(4).2018.10
-
Article InfoVolume 15 2018, Issue #4, pp. 123-134
- Cited by
- 2220 Views
-
1093 Downloads
This work is licensed under a
Creative Commons Attribution 4.0 International License
The stock market represents complex systems where multiple agents interact. The complexity of the environment in the financial markets in general has encouraged the use of modeling by multi-agent platforms and particularly in the case of the stock market.
In this paper, an agent-based simulation model is proposed to study the behavior of the volume of market transactions. The model is based on the case of a single asset and three types of investor agents. Each investor can be a zero intelligent trader, fundamentalist trader or traders using historical information in the decision making process. The goal of the study is to simulate the behavior of a stock market according to the different considered endogenous and exogenous variables.
- Keywords
-
JEL Classification (Paper profile tab)C63, C88, D53, G12
-
References38
-
Tables0
-
Figures6
-
- Figure 1. Schematic diagram of the buying/selling decision-making by the agent (investor)
- Figure 2. Flow chart of the algorithm implemented for the developed model
- Figure 3. The evolution of stock market indicators (volatility, volume, price level, bankruptcy) in the case 1
- Figure 4. The evolution of stock market indicators (volatility, volume, price level, bankruptcy) in the case 2
- Figure 5. The evolution of stock market indicators (volatility, volume, price level, bankrupt) in the case 3
- Figure 6. The evolution of stock market indicators (volatility, volume, price level, bankruptcy) in the case 4
-
- Alexander, G. J., Sharpe, W. F., & Bailey, J. V. (2001). Fundamentals of investments (3rd ed.). Pearson College Division.
- Al-Suwailem, S. I. (2008). Islamic Economics in a Complex World: Explorations in Agent-based Simulation (No. 238). The Islamic Research and Teaching Institute (IRTI).
- Arthur, W. B., Holland, J. H., LeBaron, B., Palmer, R., & Tayler, P. (1997). Asset pricing under endogenous expectations in an artificial stock market. Econ. Notes, 26, 297-330.
- Boer-Sorban, K. (2008). Agent-based simulation of financial markets: a modular, continuous-time approach. Erasmus University Rotterdam.
- Caldana, M., Cova, P., & Viano, U. (2006). Multiagent.
- Campbell, J. Y., Lo, A. W., & MacKinlay, A. C. (1997). The Econometrics of Financial Markets. Princeton University Press.
- Challet, D., Marsili, M., & Zhang, Y. C. (2013). Minority games: interacting agents in financial markets (OUP Catalogue number 9780199686698 Oxford University Press).
- Chen, S. H., & Yeh, C. H. (2002). On the emergent properties of artificial stock markets: the ef-ficient market hypothesis and the rational expectations hypothesis. Journal of Economic Behavior & Organization, 49(2), 217-239.
- Chiarella, C., Dieci, R., & Gardini, L. (2002). Speculative behaviour and complex asset price dynamics: a global analysis. Journal of Economic Behavior & Organization, 49(2), 173-197.
- Derveeuw, J. (2008). Simulation multi-agents de marchés financiers (Doctoral dissertation, Université des Sciences et Technologie de Lille – Lille I).
- Ehrentreich, N. (2003). A corrected version of the santa fe institute artificial stock market model (Complexity, 23).
- Gonçales Carlos Pedro (2003). Artificial Financial Market.
- Gonçales Carlos Pedro (2005). Artificial Financial Market II – Tail Risk.
- Kim, G. R., & Markowitz, H. (1989). Investment rules, margin, and market volatility. Journal of Portfolio Management, 16(1), 45-52.
- Kumar, P. N., Jha, A., Gautham, T. K., Mohan, J., Rama Subramanian, A. J., & Mohandas, V. P. (2010). A survey of call market (discrete) agent based artificial stock markets. Int. J. Comput. Sci. Eng., 2(09), 3025-3032.
- Lahrichi, Y. (2013). Marchés financiers: bourse, portefeuille & produits dérivés. Afrique Orient.
- LeBaron, B. (2000). Agent-based computational finance: Suggested readings and early research. Journal of Economic Dynamics and Control, 24(5-7), 679-702.
- LeBaron, B. (2001). A builder’s guide to agent-based financial markets. Quantitative Finance, 1(2), 254-261.
- LeBaron, B. (2001). Empirical regularities from interacting long-and short-memory investors in an agent-based stock market. IEEE transactions on evolutionary computation, 5(5), 442-455.
- LeBaron, B. (2001). Evolution and time horizons in an agent-based stock market. Macroeconomic Dynamics, 5(02), 225-254.
- LeBaron, B. (2002). Building the Santa Fe artificial stock market (Working Paper, Graduate). School of International Economics and Finance, Brandeis.
- LeBaron, B. (2011). Active and passive learning in agent-based financial markets. Eastern Economic Journal, 37(1), 35-43.
- Levy, H., Levy, M., & Solomon, S. (2000). Microscopic simulation of financial markets: from investor behavior to market phenomena. Elsevier.
- Lovric, M. (2011). Behavioral finance and agent-based artificial markets. Erasmus University Rotterdam.
- Lux, T., & Marchesi, M. (1999). Scaling and criticality in a stochastic multi-agent model of a financial market. Nature, 397(6719), 498-500.
- Lux, T., & Marchesi, M. (2000). Volatility clustering in financial markets: a microsimulation of interacting agents. International journal of theoretical and applied finance, 3(04), 675-702.
- Macal, C. M., & North, M. J. (2010). Tutorial on agent-based modelling and simulation. Journal of Simulation, 4(3), 151-162.
- Marchesi, M., Cincotti, S., Focardi, S., & Raberto, M. (2000). Development and testing of an artificial stock market. Proceedings Urbino.
- Naciri, N., & Tkiouat, M. (2016). Economic Agent Based Models. International Journal of Applied Engineering Research, 11(8), 5492-5502.
- Naciri, N., & Tkiouat, M. (2015). Understanding complexity in economic systems with agent based modeling. International Journal of Latest Research in Science and Technology, 4(3), 28- 31.
- Palmer, R. G., Arthur, W. B., Holland, J. H. et al. (1999). An artificial stock market. Artif Life Robotics, 3(1), 27-31.
- Raberto, M., Cincotti, S., Focardi, S. M., & Marchesi, M. (2001). Agent-based simulation of a financial market. Physica A: Statistical Mechanics and its Applications, 299(1-2), 319-327.
- Samanidou, E., Zschischang, E., Stauffer, D., & Lux, T. (2007). Agent-based models of financial markets. Reports on Progress in Physics, 70(3), 409.
- Stauffer, D. (2001). Percolation models of financial market dynamics. Advances in Complex Systems, 4(01), 19-27.
- Stigler, G. J. (1964). Public regulation of the securities markets. The Journal of Business, 37(2), 117-142.
- Tesfatsion, L. (2001). Introduction to the special issue on agent-based computational economics. Journal of Economic Dynamics and Control, 25(3-4), 281-293.
- Tesfatsion, L. (2001). Agent-based computational economics: A brief guide to the literature. In Reader’s Guide to the Social Sciences (Volume 1). Fitzroy-Dearborn.
- Tesfatsion, L. (2002). Agent-based computational economics: Growing economies from the bottom up. Artificial life, 8(1), 55-82.