  The main contribution of the paper is to employ the financial market network
as a useful tool to improve the portfolio selection process, where nodes
indicate securities and edges capture the dependence structure of the system.
Three different methods are proposed in order to extract the dependence
structure between assets in a network context. Starting from this modified
structure, we formulate and then we solve the asset allocation problem. We find
that the portfolios obtained through a network-based approach are composed
mainly of peripheral assets, which are poorly connected with the others. These
portfolios, in the majority of cases, are characterized by an higher trade-off
between performance and risk with respect to the traditional Global Minimum
Variance (GMV) portfolio. Additionally, this methodology benefits of a
graphical visualization of the selected portfolio directly over the graphic
layout of the network, which helps in improving our understanding of the
optimal strategy.
