Many complex systems display fluctuations between alternative states in correspondence to tipping points. These critical shifts are usually associated with generic empirical phenomena such as strengthening correlations between entities composing the system. In finance, for instance, market...

We study the international interbank market through a geometrical and a topological analysis of empirical data. The geometrical analysis of the time series of cross-country liabilities shows that the systematic information of the interbank international market is contained in a space of small...

The recent financial crisis has stressed the need to understand financial systems as networks of interdependent countries, where crossborder financial linkages play the fundamental role. It has also been emphasized that the relevance of these networks relies on the representation of changes...

We develop a minimalist compartmental model to analyze policies on mobility restriction in Italy during the COVID-19 outbreak. Our findings show that a early lockdowns barely shift the epidemic in time: moreover, beyond a critical value of the lockdown strength, an epidemic that seems to be...

Robot advisory services are rapidly expanding, responding to a growing interest people have in directly managing their savings. Robot advisors may reduce costs and improve the quality of the service, making user involvement more transparent. However, they may underestimate market risks,...

By exploiting a bipartite network representation of the relationships between mutual funds and portfolio holdings, we propose an indicator that we derive from the analysis of the network, labelled the Average Commonality Coefficient (ACC), which measures how frequently the assets in the fund...

We propose a distress measure for national banking systems that incorporates not only banks' CDS spreads, but also how they interact with the rest of the global financial system via multiple linkage types. The measure is based on a tensor decomposition method that extracts an adjacency matrix...

The assessment of the health impacts of the COVID-19 pandemic requires the consideration of mobility networks. To this aim, we propose to augment spatio-temporal point process models with mobility network covariates. We show how the resulting model can be employed to predict contagion patterns...