We describe a class of quantitative credit risk models that take account of the unavoidable gaps in investors' information. These incomplete information models are structural/reduced form hybrids. They combine the best features of both traditional approaches while avoiding many of their shortcomings

This study focuses on estimating credit rating migration probabilities using a continuous-record approach while controlling for the effects of idiosyncratic and systematic risk factors. Short- and long-run relationships between asset quality and obligor ratings are modeled and quantified using...

Cost and profit efficiency (CE and PE) are key to evaluate bank performance. But efficiency improvements may imply deteriorating profitability and excessive risk-taking. The dynamic reactions of performance in response to efficiency changes remain unclear on both theoretical and empirical...

A credit derivative is a path dependent contingent claim on the aggregate loss in a portfolio of credit sensitive securities. We estimate the value of a credit derivative by Monte Carlo simulation of the affine point process that models the loss. We consider two algorithms that exploit the...

This paper proposes a machine learning approach to estimate physical forward default intensities. Default probabilities are computed using artificial neural networks to estimate the intensities of the inhomogeneous Poisson processes governing default process. The major contribution to previous...

Firm-level default models are important for bottomup modeling of the default risk of corporate debt portfolios. However, models in the literature typically have several strict assumptions which may yield biased results, notably a linear effect of covariates on the log-hazard scale, no...

This paper constructs a leading macroeconomic indicator from microeconomic data using recent machine learning techniques. Using tree-based methods, we estimate probabilities of default for publicly traded non-financial firms in the United States. We then use the cross-section of out-of-sample...

In banking practice, rating transition matrices have become the standard approach of deriving multi-year probabilities of default (PDs) from one-year PDs, the latter normally being available from Basel ratings. Rating transition matrices have gained in importance with the newly adopted IFRS 9...

This paper proposes a simple technical approach for the analytical derivation of Point-in-Time PD (probability of default) forecasts, with minimal data requirements. The inputs required are the current and future Through-the-Cycle PDs of the obligors, their last known default rates, and a...

Purpose: This article explores the prediction of bankruptcy of Greek companies, in particular of the manufacturing industry, wholesale, retail and service sectors. Design/methodology/approach: The Probit model was developed so as to try to highlight the differences in the predictive capacity of...