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...

We investigate the pricing of sovereign credit risk over the period 2008-2010 for selected advanced economies by examining two widely-used indicators: sovereign credit default swap (CDS) and relative asset swap (RAS) spreads. Cointegration analysis suggests the existence of an imperfect market...

We study the link between the probability of default implied by Credit Default Swaps (CDS) spreads and the final prices of the defaulted bonds as established at the CDS settlement auctions. We observe that the post-default recovery rates at the observed spreads imply markets were often...

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...

We find that Credit Rating Agencies (CRA)'s opinions have an impact in the cost of funding of sovereign issuers and consequently ratings are a concern for financial stability. While ratings produced by the major CRAs perform reasonably well when it comes to rank ordering default risk among...

This paper studies a novel type of misallocation of credit between investments of varying liquidity. One type of investment is more liquid, i.e., its return is more pledgeable, and the other is more productive. Low liquidities of both investment types imply that the allocation of credit is...

In reduced-form pricing models, it is usual to assume a fixed recovery rate to obtain the probability of default from credit default swap prices. An alternative credit risk measure is proposed here: the maximum recovery rate compatible with observed prices. The analysis of the recent debt crisis...

Climate change is an existential threat to the world economy like no other, with complex, evolving and nonlinear dynamics that remain a source of great uncertainty. There is a bourgeoning literature on the economic impact of climate change, but research on how climate change affects sovereign...

ROC and CAP analysis are alternative methods for evaluating a wide range of diagnostic systems, including assessments of credit risk. ROC analysis is widely used in many fields, but in finance CAP analysis is more common. We compare the two methods, using as an illustration the ability of the...

Credit rating agencies face a difficult trade-off between delivering both accurate and stable ratings. In particular, its users have consistently expressed a preference for rating stability, driven by the transactions costs induced by trading when ratings change frequently. Rating agencies...