Financial technologies, boosted by the availability of machine learning models, are expanding in all areas of finance: from payments (peer to peer lending) to asset management (robot advisors) to payments (blockchain coins). Machine learning models typically achieve a high accuracy at the...

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...

We construct a network-based turbulence score that proves useful for analyzing the relationship between financial interconnectedness, and global market risk, and for identifying systemically important markets, with the highest contribution to financial turbulence. We apply our measure to study...

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 aims to assess, from an empirical viewpoint, the advantages of a stablecoin whose value is derived from a basket of underlying currencies, against a stablecoin which is pegged to the value of one major currency, such as the dollar. To this aim, we first find the optimal weights of the...