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 paper examines the relationships among market assets during stressful times, using two recently proposed econometric modeling techniques for tail risk measurement: the extreme downside hedge (EDH) and the extreme downside correlation (EDC). We extend both measures taking into account the...

A key point in the application of data science models is the evaluation of their accuracy. Statistics and machine learning have provided, over the years, a number of summary measures aimed at measuring the accuracy of a model in terms of its predictions, such as the Area under the ROC curve and...

We propose a novel systemic risk measurement model based on stochastic processes, correlation networks and conditional probabilities of default.For each country we consider three different economic sectors (sovereigns, corporates, banks) and we model each of them as a linear combination of two...

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...