We study the relationship between the risk of default and Environmental, Social and Governance (ESG) factors using Supervised Machine Learning (SML) techniques on a cross-section of European listed companies. Our proxy for credit risk is the z-score originally proposed by Altman (1968). We...

We provide new empirical evidence that U.S. expected growth and consumption volatility are closely related to the strong co-movement in sovereign spreads. We rationalize these findings in an equilibrium model with recursive utility for CDS spreads. The framework nests a reduced-form default...

This work empirically examines six structural models of the term structure of credit risk spreads: Merton (1974), Longstaff & Schwartz (1995) (with and without stochastic interest rates), Leland & Toft (1996), Collin-Dufresne & Goldstein (2001), and a constant elasticity of variance model. The...

If the creditworthiness of a counterparty is a derivative of a commodity price, there is the potential to have right- or wrong-way exposures in respective commodity transaction. Identifying them is important, because otherwise credit costs might be inadequately calculated and wrong incentives...

We investigate whether the spread of corporate debt contacts can be explained by their ultimate recovery rates. Using the actual realized recovery rates of defaulted debt instruments issued in the U.S. from 1962 to 2007, we find that recovery rate is reflected in the spread at issuance, and that...

In their work, Brigo and Capponi (2010) introduce a numerical approach for calculating credit valuation adjustments (CVA) for credit default swaps (CDS). In contrast to previous research, they consider the default of the party doing the calculation, and its correlation to the defaults of the...

We consider the modelling of credit migration risk and the pricing of migration derivatives. This enlarges the traditional setup where credit risk is based on a specificate migration state, i.e. the default one. To construct a Point-in-Time rating migration matrix as underlying value for the...

We study the relationship between the risk of default and Environmental, Social and Governance (ESG) factors using Supervised Machine Learning (SML) techniques on a crosssection of European listed companies. Our proxy for credit risk is the z-score originally proposed by Altman (1968). We...

We study the relationship between the risk of default and Environmental, Social and Governance (ESG) factors using Supervised Machine Learning (SML) techniques on a cross-section of European listed companies. Our proxy for credit risk is the z-score originally proposed by Altman (1968).We...