Publication detail

Vacha L., Barunik J. Vosvrda M.: Sentiment Patterns in the Heterogeneous Agent Model

Author(s): doc. PhDr. Jozef Baruník Ph.D.,
Mgr. Lukáš Vácha Ph.D.,
prof. Ing. Miloslav Vošvrda CSc.,
Type: Articles in journals with impact factor
Year: 2009
Number: 3
Published in: Prague Economic Papers 3, pp. 209-219 PDF
Publishing place:
Keywords: heterogeneous agent model, market structure, smart traders, Hurst exponent
JEL codes: C15, D84, G14
Suggested Citation: Vacha L., Barunik J. Vosvrda M. (2009): Sentiment Patterns in the Heterogeneous Agent Model, Prague Economic Papers 3:209-219
Grants: 402/09/0965: New Approaches for monitoring and prediction of capital markets GAUK 46108: New Nonlinear Capital Markets Theories: Fractal, Bifurcational and Behavioral Approach IES Research Framework Institutional task (2005-2011) Integration of the Czech economy into European union and its development
Abstract: In this paper we extended the original model of heterogeneous agent model by introducing smart traders and changes in the agents sentiment to the model. The idea of the smart traders is based on endeavor of the market agents to estimate the future price movements. By adding smart traders and sentiment changes we try to improve the original heterogeneous agents model so it will be able to come to closer description of the real markets. The main result of the simulations is that probability distribution functions of the price deviation changes significantly with adding smart traders to the model, and it also changes significantly with introduction of the sentiment changes. We use also Hurst exponent to measure the persistence of the price deviations and we find that the Hurst exponent is significantly increasing with smart traders in simulations. This means that the introduction of smart traders concept into the model results in significantly higher persistence of the simulated price deviations. On the other hand, introduction of changing sentiment in the proposed form does not change the persistence of simulated prices significantly.




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