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Issue: Volume 6/Number 2, Summer 2010
Research Papers
The value of non-financial information in SME risk management
Few studies that have focused on developing credit risk models specifically for small and medium-sized enterprises (SMEs) have included non-financial information as a predictor of company creditworthiness. In this study we have available non-financial, regulatory compliance and "event" data to supplement the limited accounting data that is often available for non-listed firms. We employ a sample consisting of over 5.8 million sets of accounts of unlisted firms, of which over 66,000 failed during the period 2000-2007. We find that data relating to legal action by creditors to recover unpaid deb ...  |
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Issue: Volume 6/Number 2, Summer 2010
Research Papers
A statistical modeling approach to building an expert credit risk rating system
This paper presents an efficient method for extracting expert knowledge when building a credit risk rating system. Experts are asked to rate a sample of counterparty cases according to creditworthiness. Next, a statistical model is used to capture the relation between the characteristics of a counterparty and the expert rating. For any counterparty the model can identify the rating, which would be agreed upon by the majority of experts. Furthermore, the model can quantify the concurrence among experts. The approach is illustrated by a case study regarding the construction of an application sco ... |
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Issue: Volume 6/Number 2, Summer 2010
Research Papers
Tests of the performance of structural models in bankruptcy prediction
In this study we investigate the relative performance of six structural credit risk models in predicting bankruptcy. The six models studied (the Merton, Black-Cox, Leland-Toft, Longstaff-Schwartz, flat barrier and Geske models) cover nested assumptions, thereby allowing us to study the factors that affect the accuracy of bankruptcy prediction. Using data from the period 1983-2002 (prior to the Sarbanes-Oxley Act), we compare the performance of these models for various prediction horizons and identify the factors that have the most substantial prediction power of default. Our results suggest th ... |
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Issue: Volume 6/Number 2, Summer 2010
Research Papers
Corporate bond defaults are consistent with conditional independence
Standard credit risk models rely on a doubly stochastic structure. Conditional on the evolution of common factors, defaults are independent. Recent tests have cast doubt on the empirical validity of this assumption. We modify their estimation approach in two ways. First, we model intra-month patterns in observed defaults. Second, we estimate default intensities on an out-of-sample basis, which brings our estimates closer to the ones that financial institutions would have used when implementing the approach in the past. Once intensity estimation is modified in these ways the validity of the dou ... |
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Issue: Volume 6/Number 2, Summer 2010
Comment
LETTER FROM THE EDITOR-IN-CHIEF
In this issue we present two full-length research papers and two technical reports.We are pleased to include two papers co-authored by very prominent contributors in the field: Edward Altman and Frank Fabozzi. The first paper, "Corporate bond defaults are consistent with conditional independence", is by Kramer. The paper reconsiders the results in Das, Duffie, Kapadia and Saita (2007), which cast doubt on the empirical validity of the conditional independence assumption in the widely used doubly stochastic model of credit risk. The authors show that the result of Das et al is not robust to alt ...  |
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