We propose a tractable model of a firm's dynamic debt and equity issuance policies in the presence of asymmetric information. Because "investment-grade" firms can access debt markets, managers who observe a bad private signal can both conceal this information and shield shareholders from...

How does bank distress impact their customers' probability of default and trade credit availability? We address this question by looking at a unique sample of German firms from 2000 to 2011. We follow their firm-bank relationships through times of distress and crisis, featuring the different...

Most studies focusing on the determinants of loss given default (LGD) have largely ignored possible lagged effects of the macroeconomy on LGD. We fill this gap by employing a wide set of macroeconomic covariates on a retail portfolio that represents 15% of the Czech consumer credit market over...

Bharath and Shumway (2008) provide evidence that shows that it is the functional form of Merton’s (1974) distance to default (DD) model that makes it useful and important for predicting defaults. In this paper, we investigate whether the default predictability of the Merton DD model would be...

On 3 December EY hosted a SUERF conference on banking reform with Sir Howard Davies, the Chairman of RBS, and Dame Colette Bowe, the Chairman of the Banking Standards Board, as the two keynote speakers. Professor David Miles (Imperial College) gave the SUERF 2015 Annual Lecture on Capital and...

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...

Using a large sample of business groups from more than one hundred countries around the world, we show that group information matters for parent and subsidiary default prediction. Group firms may support each other when in financial distress. Potential group support represents an off-balance...

This paper investigates a model of strategic interactions in financial networks, where the decision by one agent on whether or not to default impacts the incentives of other agents to escape default. Agents' payoffs are determined by the clearing mechanism introduced in the seminal contribution...

Accurate probability-of-distress models are central to regulators, firms, and individuals who need to evaluate the default risk of a loan portfolio. A number of papers document that recent machine learning models outperform traditional corporate distress models in terms of accurately ranking...

This paper investigates a model of strategic interactions in financial networks, where the decision by one agent on whether or not to default impacts the incentives of other agents to escape default. Agents' payoffs are determined by the clearing mechanism introduced in the seminal contribution...