Endogenous Derivation and Forecast of Lifetime PDs
16 Pages Posted: 30 Jun 2015 Last revised: 14 Jul 2015
Date Written: July 14, 2015
This paper proposes a simple technical approach for the derivation of future (forward) point-in-time PD forecasts, with minimal data requirements. The inputs required are the current and future through-the-cycle PDs of the obligors, their last known default rates, and a measure for the systematic dependence of the obligors. Technically, the forecasts are made from within a classical asset-based credit portfolio model, just with the assumption of a suitable autoregressive process for the systematic factor. The paper discusses in detail the practical issues of implementation, in particular the parametrization alternatives.
The paper also shows how the approach can be naturally extended to low-default portfolios with volatile default rates, using Bayesian methodology. Furthermore, the expert judgments about the current macroeconomic state, although not necessary for the forecasts, can be embedded using the Bayesian technique.
The presented forward PDs can be used for the derivation of lifetime credit losses required by the new accounting standard IFRS 9. In doing so, the presented approach is endogenous, as it does not require any exogenous macroeconomic forecasts which are notoriously unreliable and often subjective.
Keywords: Prediction, Probability of Default, PD, Default Rates, Through-the-Cycle, TTC, Point-in-Time, PIT, Credit Portfolio Model, Systematic Factor, Macroeconomic Factor, Time Series, Autoregression, Bayesian Analysis, IFRS 9, Accounting, Financial Instruments, Lifetime, Expected Credit Losses
JEL Classification: C13, C11, C22, C51, C53, E32, E37, M41, G33
Suggested Citation: Suggested Citation