The impact of corporate social and environmental performance on credit rating prediction: North America versus Europe
The authors quantify the extent to which the quality of credit rating predictions improves by integrating measures of corporate social performance (CSP) in an established credit risk model. Their analysis provides comprehensive evidence of the…
Elliptical and Archimedean copula models: an application to the price estimation of portfolio credit derivatives
This paper explores the impact of elliptical and Archimedean copula models on the valuation of basket default swaps.
This paper presents an International Financial Reporting Standard 9 (IFRS 9) compliant solution related to expected credit loss modeling.
The Covid-19 health crisis has dramatically affected just about every aspect of the economy, including the transition from a record long benign credit cycle to a stressed one, with still uncertain dimensions. This paper seeks to assess the credit climate…
Carbon pricing paths to a greener future, and potential roadblocks to public companies’ creditworthiness
In this paper, the authors introduce a valuation-based approach to estimate how energy transition risk may impact the creditworthiness of public companies globally within the next thirty years.
In this study, the authors identify the three types of risks involved in an art-secured lending operation and present a framework to assess their combined effects via a Monte Carlo simulation.
This study compares the gradient-boosting model with four other well-known classifiers, namely, a classification and regression tree (CART), logistic regression (LR), multivariate adaptive regression splines (MARS) and a random forest (RF).
This work looks at a wide range of models to test the degree to which CECL is procyclical for different types of model.
In this paper, we investigate the alpha factor’s sensitivity to key model parameters under stylized portfolio assumptions in order to better understand its complex characteristics. Our analysis is based on the numerical simulation of alpha sensitivities…
Creditworthiness of individual entities may offer an insight into systemic risk of financial markets
Recently developed techniques aimed at answering interpretability issues in neural networks are tested and applied to a retail banking case
One clearing member's disproportionately large position increases the credit risk for all CCP members
In cost-of-capital computations, credit risk is only taken into consideration at the level of the debt beta approach. We show that applications of the debt beta approach in company valuation suffer from unrealistic assumptions about the market index and…
The authors establish that the combination of lifetime ECL and the Basel Capital Adequacy Framework, which relies on a one-year horizon, results in capital overestimation. Alongside this finding, and in order to alleviate the problem, they propose two…
In this paper, we present an analytical expression for CVA with WWR under the assumption of the lognormally distributed trade value.
This paper considers a definition of through-the-cycle as independent from an economic state that can result in a time-varying TTC probability of default.
This study investigates the systematic error that is made if the exposure pool underlying a default time series is assumed to be homogeneous when in reality it is not.
In this paper, the authors employ a hybrid approach to design a practical and effective CRE model based on a deep belief network (DBN) and the K-means method.
Pierre Henry-Labordère applies neural networks to a control problem approach for managing collateral
This paper develops a parsimonious model for evaluating portfolio credit derivatives dependent on aggregate loss.
This paper proposes an efficient method to obtain the distribution of the CVA at a given risk horizon, from which risk measures such as the CVA VaR can be computed.
Application scoring plays a critical role in determining the future quality of a lender’s book. It is therefore important to monitor the performance of an application scorecard to ensure it performs as expected.