This paper presents a backtesting framework for a probability of default (PD) model,
assuming that the latter is calibrated to both point-in-time (PIT) and through-the-cycle (TTC) …

Analysts often find themselves working with less than perfect development and/or validation
samples, and data issues typically affect the interpretation of default prediction validation …

The Basel Accords require financial institutions to regularly validate their loss given default
(LGD) models. This is crucial so banks are not misestimating the minimum required capital …

The aim of validating default probabilities is to analyze whether these are not too low. For
small sample sizes, however, there are not enough observations available to detect …

The paper argues for the need for and importance of the dual calibration of a probability of
default (PD) model (ie, calibration to both point-in-time (PIT) and through the-cycle (TTC) PD …

We conduct a systematic comparison of confidence intervals around estimated probabilities
of default (PD), using several analytical approaches from large-sample theory and …

We investigate the puzzle in the literature that various parametric loss given default (LGD)
statistical models perform similarly, by comparing their performance in a simulation …

In this study we consider the construction of through-the-cycle (“TTC”) probability-of-default
(“PD”) models designed for credit underwriting uses and point-in-time (“PIT”) PD models …

In the recent paper “A methodology for point-in-time-through-the-cycle probability of default
decomposition in risk classification systems”(Carlehed and Petrov 2012) in this journal …