Modelling an Artificial Financial Market: Agent Based Approach
Öz
The traditional view of perfect rationality and homogeneity in finance and economics has been challenged by growing evidence on the theoretical limitations and empirical findings. That leads a paradigm shift from representing agents with rational expectations to boundedly rational agent having heterogenous expectations. In this regard, this study aims to model a financial market with agent-based approach to deal better with heterogeneity over agents and to capture the interaction among them.
A primitive agent-based artificial financial market is created based on the Genoa market model introduced by Raberto et al., (2001). We aim to replicate the stylized fact of financial asset returns to assure validity of model. Agents are endowed with prespecified cash and assets amount. Agents based simulation is run under different scenarios and results are examined. Agents differ when trading as being noise trader or an agent using technical trading. The model was able to replicate leptokurtic shape of probability density function, absence of autocorrelation and volatility clustering.
Anahtar Kelimeler
Artificial Financial Market, Agent Based Simulation, Heterogenous Agents
Kaynakça
- Alfi, V., M. Cristelli, L. Pietronero, and A. Zaccaria (2009), Minimal agent based model for financial markets I: origin and self-organization of stylized fatcs, The European Physical Journal B, 67(3), 385– 397.
- Aloud, M., E. Tsang, and R. Olsen (2012), Modelling the FX market traders’ behaviour: an agentbased approach, Chapter 15, in Simulation in Computational Finance and Economics: Tools and Emerging Applications, edited by B. Alexandrova-Kabadjova, S. Martinez-Jaramillo, A. Garcia-Almanza, and E. Tsang, IGI Global, Hershey, Pennsylvania, 202-228.
- Arifovic, J. (1994), Genetic algorithm learning and the cobweb model, Journal of Economic Dynamics & Control, 18, 3–28
- Arifovic, J. (2001), Evolutionary dynamics of currency substitution, Journal of Economic Dynamics & Control, 25, 395–417.
- Arthur, W. (1991), Designing economic agents that act like human agents: a behavioral approach to bounded rationality, American Economic Review, 81, 353–359.
- Arthur, W. B., J. H. Holland, B. LeBaron, R. Palmer, and P. Tayler (1997), Asset pricing under endogenous expectations in an artificial stock market, in The economy as an evolving, complex system II, edited by W. Arthur, D. Lane, and S. Durlauf, pp. 15–44, Addison Wesley, Redwood City, CA
- Bachlier, L. (1964), Theory of speculation in the random character of stock market prices, MIT Press,Cambridge.
- Bouchaud, J. P., & Cont, R. (2000). Herd behaviour and aggregate fluctuations in financial market. Macroeconomic Dynamics, 2, 170-196.
- Brooks, C. (1996), Testing for non-linearity in daily sterling exchange rates, Applied Financial Economics, 6(4), 307–317
- Cincotti, S., Focardi, S. M., Marchesi, M., & Raberto, M. (2003). Who wins? Study of long-run trader survival in an artificial stock market. Physica A: Statistical Mechanics and its Applications, 324(1-2), 227-233.