  We propose a model for stochastic formation of opinion clusters, modelled by
an evolving network, and herd behaviour to account for the observed fat-tail
distribution in returns of financial-price data. The only parameter of the
model is h, the rate of information dispersion per trade, which is a measure of
herding behavior. For h below a critical h* the system displays a power-law
distribution of the returns with exponential cut-off. However for h>h* an
increase in the probability of large returns is found, and may be associated to
the occurrence of large crashes.
