Systemic Risk Analysis on Reconstructed Economic and Financial Networks.
We address a fundamental problem that is systematically encountered when modeling real-world complex systems of societal relevance: the limitedness of the information available. In the case of economic and financial networks, privacy issues severely limit the information that can be accessed and, as a consequence, the possibility of correctly estimating the resilience of these systems to events such as financial shocks, crises and cascade failures. Here we present an innovative method to reconstruct the structure of such partially-accessible systems, based on the knowledge of intrinsic node-specific properties and of the number of connections of only a limited subset of nodes. This information is used to calibrate an inference procedure based on fundamental concepts derived from statistical physics, which allows to generate ensembles of directed weighted networks intended to represent the real system-so that the real network properties can be estimated as their average values within the ensemble. We test the method both on synthetic and empirical networks, focusing on the properties that are commonly used to measure systemic risk. Indeed, the method shows a remarkable robustness with respect to the limitedness of the information available, thus representing a valuable tool for gaining insights on privacy-protected economic and financial systems.
Istituto dei Sistemi Complessi (ISC-CNR) UoS "Sapienza" Università di Roma, 00185 Rome, Italy.
Giulio
G
Cimini
Istituto dei Sistemi Complessi (ISC-CNR) UoS "Sapienza" Università di Roma, 00185 Rome, Italy.
Tiziano
T
Squartini
Lorentz Institute for Theoretical Physics, University of Leiden, 9506 Leiden, Netherlands.
Diego
D
Garlaschelli
Istituto dei Sistemi Complessi (ISC-CNR) UoS "Sapienza" Università di Roma, 00185 Rome, Italy.|IMT Institute for Advanced Studies, 55100 Lucca, Italy.
Andrea
A
Gabrielli