  We extend the well-known Cont-Bouchaud model to include a hierarchical
topology of agent's interactions. The influence of hierarchy on system dynamics
is investigated by two models. The first one is based on a multi-level, nested
Erdos-Renyi random graph and individual decisions by agents according to Potts
dynamics. This approach does not lead to a broad return distribution outside a
parameter regime close to the original Cont-Bouchaud model. In the second model
we introduce a limited hierarchical Erdos-Renyi graph, where merging of
clusters at a level h+1 involves only clusters that have merged at the previous
level h and we use the original Cont-Bouchaud agent dynamics on resulting
clusters. The second model leads to a heavy-tail distribution of cluster sizes
and relative price changes in a wide range of connection densities, not only
close to the percolation threshold.
