The two main issues for managing wrong way risk (WWR) for the credit valuation adjustment (CVA, i.e. WW-CVA) are calibration and hedging. Hence we start from a novel model-free worst-case approach based on static hedging of counterparty exposure with liquid options. We say "start from" because...

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...

We propose an econometric model for predicting the share of bank debt held by bankrupt firms by combining a novel set of firm-level financial variables and macroeconomic indicators. Our firm-level data include payment remarks in the form of debt collections from private agencies and attachments...

In credit default prediction models, the need to deal with time-varying covariates often arises. For instance, in the context of corporate default prediction a typical approach is to estimate a hazard model by regressing the hazard rate on time-varying covariates like balance sheet or stock...

Credit risk measurement and management become more important in all financial institutions in the light of the current financial crisis and the global recession. This particularly applies to most of the complex structured financing forms whose risk cannot be quantified with com-mon rating...

In the context of macroeconomic uncertainty and liquidity problems existing on international markets, expanding the banking system leads to amplification interferences of a broad spectrum of risks. This article delineates the recent area of researchers’ interest in the domain of credit risk...

A standard quantitative method to access credit risk employs a factor model based on joint multi- variate normal distribution properties. By extending a one-factor Gaussian copula model to make a more accurate default forecast, this paper proposes to incorporate a state-dependent recovery rate...

The use of probability of default estimates to assess the risks of a credit portfolio should not ignore estimation uncertainty. The latter can be quantified by confidence intervals. But assumptions about dependencies of these intervals are inconsistent with assumptions of conventional credit...