Wealth distribution across communities of adaptive financial agents
Authored by Pietro DeLellis, Franco Garofalo, Iudice Francesco Lo, Elena Napoletano
Date Published: 2015
DOI: 10.1088/1367-2630/17/8/083003
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Abstract
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.
Tags
transaction taxes
Heterogeneous agents
multiagent model
Stock-market behavior