A Model of Financial Market Dynamics with Heterogeneous Beliefs and State-Dependent Confidence
- 129 Downloads
In a simple model of financial market dynamics, we allow the price of a risky security to be set by a market maker depending on the excess demand of heterogeneous interacting traders, fundamentalists and chartists, who place their orders based upon different expectations schemes about future prices: while chartists rely on standard trend-based rules, fundamentalists are assumed to know the economic environment and to form their beliefs accordingly. As price moves away from the long-run fundamental, fundamentalists become less confident in their forecasts, and put increasing weight on a reversion towards the fundamental price. The resulting two-dimensional discrete time dynamical system can exhibit a rich range of dynamic scenarios, often characterized by coexistence of attractors. A simple noisy version of the model reveals a variety of possible patterns for return time series.
KeywordsHeterogeneous beliefs Financial market dynamics Bifurcation analysis Coexisting attractors
JEL ClassificationsC62 D84 E32 G12
Unable to display preview. Download preview PDF.
- Chiarella C., He X.-Z. (2003) Heterogeneous beliefs, risk and learning in a simple asset pricing model with a market maker. Macroeconomic Dynamics 7: 503–536Google Scholar
- Chiarella C., Khomin A. (2000) The dynamic interaction of rational fundamentalists and trend chasing chartists in a monetary economy. In: Delli Gatti D., Gallegati M., Kirman A.(eds) Interaction and market structure: Essays on heterogeneity in economics. Springer, Berlin, pp 151–165Google Scholar
- De Grauwe P., Dewachter H., Embrechts M. (1993) Exchange rate theories. Chaotic models of the foreign exchange market. Blackwell, OxfordGoogle Scholar
- Gaunersdorfer, A., Hommes, C. H., & Wagener, F. (2003). Bifurcation routes to volatility clustering under evolutionary learning. Technical Report No. 03-03, CeNDEF, University of Amsterdam.Google Scholar
- Hommes C.H. (2006) Heterogeneous agent models in economics and finance. In: Judd K.L., Tesfatsion L.(eds) Handbook of computational economics, volume 2: Agent-based computational economics. North-Holland, Amsterdam, pp 1109–1186Google Scholar
- LeBaron B. (2006) Agent-based computational finance. In: Judd K.L., Tesfatsion L.(eds) Handbook of computational economics, volume 2: Agent-based computational economics. North-Holland, Amsterdam, pp 1187–1234Google Scholar
- Tong H. (1990) Nonlinear time-series. A dynamical system approach. Clarendon Press, OxfordGoogle Scholar