  This paper studies the trading volumes and wealth distribution of a novel
agent-based model of an artificial financial market. In this model,
heterogeneous agents, behaving according to the Von Neumann and Morgenstern
utility theory, may mutually interact. A Tobin-like tax (TT) on successful
investments and a flat tax are compared to assess the effects on the agents'
wealth distribution. We carry out extensive numerical simulations in two
alternative scenarios: i) a reference scenario, where the agents keep their
utility function fixed, and ii) a focal scenario, where the agents are adaptive
and self-organize in communities, emulating their neighbours by updating their
own utility function. Specifically, the interactions among the agents are
modelled through a directed scale-free network to account for the presence of
community leaders, and the herding-like effect is tested against the reference
scenario. We observe that our model is capable of replicating the benefits and
drawbacks of the two taxation systems and that the interactions among the
agents strongly affect the wealth distribution across the communities.
Remarkably, the communities benefit from the presence of leaders with
successful trading strategies, and are more likely to increase their average
wealth. Moreover, this emulation mechanism mitigates the decrease in trading
volumes, which is a typical drawback of TTs.
