The paper presents a new methodology, based on tensor decomposition, to map dynamic trade networks and to assess their strength on spreading economic fluctuations at different periods of time in Asia. Using the monthly merchandise import and export data across 33 Asian economies, together with...

This paper describes a multidimensional machine learning model and its implementation in a financial technology (fintech) application. The aim of the model is to learn from both micro economic financial data and macro economic trends the credit rating of companies that ask for credit. We show...

We propose a statistical measure, based on correlation networks, to evaluate the systemic risk that could arise from the resolution of a failing or likely-to-fail financial institution, under three alternative scenarios: liquidation, private recapitalization, or bail-in. The measure enhances the...

The paper investigates the role of network centrality in predicting borrowers' and lenders' behavior in peer-to-peer (P2P) lending. The empirical analysis of data from Renrendai, a leading lending platform in the People's Republic of China, reveals that the lenders who are at the center of a...