4 papers
ImPORTance: Machine Learning-Driven Analysis of Global Port Significance and Network Dynamics for Improved Operational Efficiency
Emanuele Carlini, Domenico Di Gangi, Vinicius Monteiro de Lira +3
Seaports play a crucial role in the global economy, and researchers have sought to understand their significance through various studies. In this paper, we aim to explore the commo…
Modelling time-varying interactions in complex systems: the Score Driven Kinetic Ising Model
Carlo Campajola, Domenico Di Gangi, Fabrizio Lillo +1
A common issue when analyzing real-world complex systems is that the interactions between the elements often change over time: this makes it difficult to find optimal models that d…
Score-Driven Exponential Random Graphs: A New Class of Time-Varying Parameter Models for Dynamical Networks
Domenico Di Gangi, Giacomo Bormetti, Fabrizio Lillo
Motivated by the increasing abundance of data describing real-world networks that exhibit dynamical features, we propose an extension of the Exponential Random Graph Models (ERGMs)…
Assessing systemic risk due to fire sales spillover through maximum entropy network reconstruction
Domenico Di Gangi, Fabrizio Lillo, Davide Pirino
Assessing systemic risk in financial markets is of great importance but it often requires data that are unavailable or available at a very low frequency. For this reason, systemic…