  The collective phenomena of a liquid market is characterized in terms of a
particle system scenario. This physical analogy enables us to disentangle
intrinsic features from purely stochastic ones. The latter are the result of
environmental changes due to a `heat bath' acting on the many-asset system,
quantitatively described in terms of a time dependent effective temperature.
The remaining intrinsic properties can be widely investigated by applying
standard methods of classical many body systems. As an example, we consider a
large set of stocks traded at the NYSE and determine the corresponding
asset--asset `interaction' potential. In order to investigate in more detail
the cluster structure suggested by the short distance behavior of the
interaction potential, we perform a connectivity analysis of the spatial
distribution of the particle system. In this way, we are able to draw
conclusions on the intrinsic cluster persistency independently of the specific
market conditions.

Disordered Systems and Neural Networks;Statistical Mechanics;Statistical Finance