The use of topological quantities to detect hierarchical properties in financial markets: the Financial sector in NYSE

In previous studies we have analyzed dynamical filtered graphs (namely the Minimum Spanning Trees and Planar Maximally Filtered Graphs) constructed from correlation matrices of daily return time series for the 300 most capitalized stocks of the New York Stock Exchange, and we have introduced centrality/peripherality synthetic indices which allowed to detect the stocks' relative positions in the network. In this paper we investigate the central role that the Financial sector is playing in the system hierarchy. We find that some Financial subsectors are particularly well clustered while others are more heterogeneous. Although most financial stocks are located in the central regions of the network, there are some notorious companies which have different behaviors and interact with more peripheral regions. We find that the stocks' relative positions are deeply related to their main economic activities.