Traditional methods for evaluating corporate credit risk rarely consider the impact of the macro economy on corporate value and performance. We argue that lenders and management can obtain valuable information about the need for and approach to restructuring by decomposing default predictions...

Climate change information, especially greenhouse gas (GHG) emissions disclosures (Scopes 1, 2 and 3), has recently attracted considerable interest from investors, companies, regulators, and other stakeholders. This study examines the relationship between voluntary scope 3 GHG emissions...

Most of the bankruptcy prediction models developed so far have in common that they are based on quantitative data or more precisely financial ratios. However, useful information can be lost when disregarding soft information. In this work, we develop an automated content analysis technique to...

Recent literature has pointed out that information asymmetries may be the reason for the poor performance of structural credit risk models to fit corporate bond data. It is well known in fact that these models lead to a strong understatement of the credit spread terms structure, particularly on...

We model 1927-1997 U.S. business failure rates using a time series approach based on unobserved components. Clear evidence is found of cyclical behavior in default rates. The cycle has a period of around 10 years. We also detect longer term movements in default probabilities and default...

The goal of the Basle II regulatory formula is to model the unexpected loss on a loan portfolio. The regulatory formula is based on an asymptotic portfolio unexpected default rate estimation that is multiplied by an estimate of the loss given default parameter. This simplification leads to a...

This paper employs the methodology of Wilson (1997) on Hungarian data to conduct a macro stress test in relation to banks' corporate loan portfolio. First, sector specific models of bankruptcy are estimated, where the bankruptcy frequency is linked to the general health of the economy. Data on...

We use a vector error correction model to study the long-term relationship between aggregate expected default frequency and the macroeconomic development, i.e. CPI, industry production and short-term interest rate. The model is used to forecast the median expected default frequency of the...

The main challenge of forecasting credit default risk in loan portfolios is forecasting the default probabilities and the default correlations. We derive a Merton-style threshold-value model for the default probability which treats the asset value of a firm as unknown and uses a factor model...

In this paper we focus on the analysis of the effect of prediction and estimation risk on the loss distribution, risk measures and economic capital. When variables for the determination of probability of default and loss distribution have to be predicted because they are not available at the...