This paper presents a framework in which many structural credit risk models can be made hybrid by randomizing the default trigger, while keeping the capital structure intact. This produces random recovery rates negatively correlated with the default probability. The approach is implemented on a...

This paper focuses on the key credit risk parameter Loss Given Default (LGD). We describe its general properties and determinants with respect to seniority of debt, characteristics of debtors or macroeconomic conditions. Further, we illustrate how the LGD can be extracted from market observable...

This paper focuses on the key credit risk parameter Loss Given Default (LGD). We describe its general properties and determinants with respect to seniority of debt, characteristics of debtors or macroeconomic conditions. Further, we illustrate how the LGD can be extracted from market observable...

We present a dialogue on Counterparty Credit Risk touching on Credit Value at Risk (Credit VaR), Potential Future Exposure (PFE), Expected Exposure (EE), Expected Positive Exposure (EPE), Credit Valuation Adjustment (CVA), Debit Valuation Adjustment (DVA), DVA Hedging, Closeout conventions,...

In this paper, we establish a comparison between one of the most traded financial derivatives in the markets, the so-called catastrophe bonds (abbreviated as cat bonds) and the corporate bonds. In the first section, we start from a brief definition as well as some basic concepts. In section two,...

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...

Higher default probabilities are associated with lower future stock returns. The anomaly cannot be explained by strategic shareholder actions, traditional risk factors, characteristics, or mispricing, but, instead, is consistent with a risk-shifting hypothesis. Consistent with the risk-shifting...

We present a stochastic simulation model for estimating forward-looking corporate probability of default and loss given default. We formulate the model in a discrete time frame, apply capital-budgeting techniques to define the relationships that identify the default condition, and solve the...

This study aims to evaluate the techniques used for the validation of default probability (DP) models. By generating simulated stress data, we build ideal conditions to assess the adequacy of the metrics in different stress scenarios. In addition, we empirically analyze the evaluation metrics...

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...