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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...
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Timely identification of coincident systemic conditions and forward-looking capacity to anticipate adverse developments are critical for macroprudential policy. Despite clear recognition of these factors in literature, an evaluation methodology and empirical tests for the information value of...
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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...
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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...
Persistent link: https://www.econbiz.de/10012845652
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...
Persistent link: https://www.econbiz.de/10012866642