Not like consumer credit scoring, corporate default study is usually jeopardized by the low-n-low-p data sizes. In the fourth chapter of their book, Gunter and Peter, demonstrated an example about how to construct prediction models for IDR (invesment g…
Tag: credit risk
The eve of Lehman Brothers’ demise
Recently Moody’s warned the US government to degrade its credit rating if the nation’s debt limit increase is not approved [Ref. 1]. The news came right after Standard & Poor’s lowered US’s sovereign rating from AAA to AA. Those rating change…
The eve of Lehman Brothers’ demise
Recently Moody’s warned the US government to degrade its credit rating if the nation’s debt limit increase is not approved [Ref. 1]. The news came right after Standard & Poor’s lowered US’s sovereign rating from AAA to AA. Those rating change…
Using Proc IML for credit risk validation
Validation step is crucial for a scorecard in credit risk industry. Gunter and Peter mentioned in their fantastic book [Ref. 1] that cumulative accuracy profile (CAP) and receiver operating characteristic (ROC) are two popular methods. Thus, the value…
A scorecard for default risk with sparkline
In the 1st chapter of their must-read credit risk modeling book, Gunter and Peter used the ratios of working capital(WC), retained earnings(RE), earnings before interest and taxes(EBIT), sales(S) and market value of equity(ME) over either total liab…
Semiparametric method in predicting loss given default
Sparse data is a big concern in building models for loss given default (LGD) for corporate risk. For LGD, most predictors are instrument-related, firm-specific, macroeconomic and industry-specific variables, while the costs to collect such data may be…
A scorecard to create transition matrices by cohort approach
Cohort approach is a widely-used method in creating transition matrices for evaluation of credit risk. In the example below, I made a macro to automate this process. Although the code is for one-year period transition matrices, scorecards for multiple…