  This is a review about financial dependencies which merges efforts in
econophysics and financial economics during the last few years. We focus on the
most relevant contributions to the analysis of asset markets' dependencies,
especially correlational studies, which in our opinion are beneficial for
researchers in both fields. In econophysics, these dependencies can be modeled
to describe financial markets as evolving complex networks. In particular we
show that a useful way to describe dependencies is by means of information
filtering networks that are able to retrieve relevant and meaningful
information in complex financial data sets. In financial economics these
dependencies can describe asset comovement and spill-overs. In particular,
several models are presented that show how network and factor model approaches
are related to modeling of multivariate volatility and asset returns
respectively. Finally, we sketch out how these studies can inspire future
research and how they contribute to support researchers in both fields to find
a better and a stronger common language.
