In this paper we investigate the effects of network topologies on asset price dynamics. We introduce network communications into a simple asset pricing model with heterogeneous beliefs. The agents may switch between several belief types according to their performance. The performance information is available to the agents only locally through their own experience and the experience of other agents directly connected to them. We model the communications with four commonly considered network topologies: a fully connected network, a regular lattice, a small world, and a random graph. The results show that the network topologies influences asset price dynamics in terms of the regions of stability, amplitudes of fluctuations and statistical properties.

In this paper we investigate the effects of network topologies on asset price dynamics. We introduce network communications into a simple asset pricing model with heterogeneous beliefs. The agents may switch between several belief types according to their performance. The performance information is available to the agents only locally through their own experience and the experience of other agents directly connected to them. We model the communications with four commonly considered network topologies: a fully connected network, a regular lattice, a small world, and a random graph. The results show that the network topologies influences asset price dynamics in terms of the regions of stability, amplitudes of fluctuations and statistical properties.

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.

We study S-shaped utility maximization for the standard portfolio selection problem with one risky and one risk-free asset. We derive a mean-variance criterium of choice, which preserves reference dependence and the reflection effect. Subsequently we study diversification possibilities and obtain the demand for the risky asset. We close the paper with an alternative interpretation of the criterium in terms of target-based decision making.

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