We compared the predictive performance of a series of machine learning and traditional methods for monthly CDS spreads, using firms' accounting-based, market-based and macroeconomics variables for a time period of 2006 to 2016. We find that ensemble machine learning methods (Bagging, Gradient...

Portfolio credit risk measurement is greatly affected by data constraints, especially when focusing on loans given to unlisted firms. Standard methodologies adopt convenient, but not necessarily properly specified parametric distributions or simply ignore the effects of macroeconomic shocks on...

Recent advances in digital technology and big data have allowed FinTech (financial technology)lending to emerge as a potentially promising solution to reduce the cost of credit and increasefinancial inclusion. However, machine learning (ML) methods that lie at the heart of FinTech credithave...

This paper presents the Systemic Risk and Interconnectedness (SyRIN) tool. SyRIN allows a comprehensive assessment of systemic risk via quantification of the impact of risk amplification mechanisms, due to interconnectedness structures across banks and other financial intermediaries-insurance,...

We use data on 1,294 banks in Central and Eastern Europe to analyze how bank ownership and creditor coordination in the form of the Vienna Initiative affected credit growth during the 2008–09 crisis. As part of the Vienna Initiative western European banks signed country-specific commitment...

Using a dataset covering a large sample of emerging economies (EMEs), westudy the relationship between debt and economic performance in bad times.While previous research has shown that private debt buildups exacerbate theduration and intensity of recessions in advanced economies (AEs), we...

This paper computes data-driven correlation networks based on the stock returns of international banks and conducts a comprehensive analysis of their topological properties. We first apply spatial-dependence methods to filter the effects of strong common factors and a thresholding procedure to...

This paper reviews the empirical relationships between credit growth, economic recovery, and bank profitability in Europe after the global financial crisis (GFC). We find that the post-GFC recoveries in Europe have been weaker than previous recoveries, with the 'double-dip' recessions in 2011-12...

Using a panel data approach for two samples of listed and unlisted European banks, this paper provides evidence that, over a decade and a half preceding the pandemic, bank dividend payouts were adjusted in line with the motivations found in the literature. Banks change their dividend payouts...

A push-pull-brake model of capital flows is used to study the effects of fiscal policy changes on private capital flows to emerging Europe during 2000-07. In the model, countercyclical fiscal policy has two opposing effects on capital inflows: (i) a conventional absorption-reducing effect, as a...