Empirical Applications of Network and Random Matrix Theories to Economic and Financial Complex Systems
This thesis contributes to the existing literature on the empirical applications of network theory and Random Matrix Theory to economic and financial complex systems. It is based on six essays which can be structured in two parts. The first part consists of four essays (from chapter 2 to chapter 5), which are devoted to various applications of network theory to large data sets of credit relationships in the interbank market and between banks and other sectors of the economy. They study various properties in different structures of different financial networks. More specifically, the second and the third chapters respectively analyze structural correlations and structural similarities in one-mode networks. The fourth chapter deals with topological and structural properties in bipartite networks, and the fifth chapter is devoted to overlaps and correlations between layers in the multilayer structure of networks. Two essays in the second part (respectively in chapter 6 and chapter 7), based on the methods of Random Matrix Theory, analyze the structure of the cross-correlation matrices of banks' loan portfolios and the structure of the cross-correlation matrix of worldwide economic sentiment indices.