Asset Price Dynamics with Local Interactions under Heterogeneous Beliefs

Abstract

This paper investigates the effect of network structure on the asset price dynamics. We propose a simple present value discounted asset pricing model with heterogeneous agents. Every period the agents choose a predictor of the future price on the basis of past performance of their own and alternative strategies and form their demands for a risky asset. The information about the performance of an alter-* We thank the participants of the workshop "Ten years of CeNDEF" for their comments and suggestions. We are also grateful to the organizers of the Seventh Trento Summer School in Agent-Based Computational Economics during which we began to work on this paper, for creating stimulating environment and for the opportunity to present our work. We thank Mikhail Anufriev, William Brock, John Duffy, Cars Hommes, Alan Kirman and Marco LiCalzi for their encouragements and suggestions. Authors are responsible for possible errors and omissions.

Does Social Interaction destabilise Financial Markets?

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Does Social Interaction Destablise Financial Markets?

“…Social influence in this case is not based on other investors' outcomes, but on their original information signals. In the same vein, Panchenko et al (2010) state that well connected investors are better off. Particularly, like in this paper, they consider the heterogeneous agent model of Brock and Hommes (1998).…”

Asset Return and Wealth Dynamics with Reference Dependent Preferences and Heterogeneous Beliefs

“…de Fontnouvelle ( 2000) enriched it with various information flow schemes about the dividend payments, while Brock et al (2005) examined an extension to many trader types. Gaunersdorfer (2000) introduced heterogeneity of beliefs with respect to the returns volatility, Hommes et al (2005) included a market maker into the market pricing mechanism, Brock et al (2006) introduced risk hedging instruments in form of Arrow securities in the model, and Panchenko et al (2007) analyzed how local interactions affect the model outcomes.…”