Calibration of structural and reduced-form recovery models

TL;DR

This paper investigates how different recovery rate models, especially those incorporating a dependence on default probabilities, affect the accuracy of loss distribution tail estimates in credit risk modeling.

Contribution

It demonstrates that modeling recovery rates as a function of default probabilities improves tail loss estimation compared to constant recovery assumptions.

Findings

Constant recovery models underestimate tail losses.

Reduced-form models perform better with full calibration data.

Functional dependence models provide the most stable results.

Abstract

In recent years research on credit risk modelling has mainly focused on default probabilities. Recovery rates are usually modelled independently, quite often they are even assumed constant. Then, however, the structural connection between recovery rates and default probabilities is lost and the tails of the loss distribution can be underestimated considerably. The problem of underestimating tail losses becomes even more severe, when calibration issues are taken into account. To demonstrate this we choose a Merton-type structural model as our reference system. Diffusion and jump-diffusion are considered as underlying processes. We run Monte Carlo simulations of this model and calibrate different recovery models to the simulation data. For simplicity, we take the default probabilities directly from the simulation data. We compare a reduced-form model for recoveries with a constant recovery approach. In addition, we consider a functional dependence between recovery rates and default probabilities. This dependence can be derived analytically for the diffusion case. We find that the constant recovery approach drastically and systematically underestimates the tail of the loss distribution. The reduced-form recovery model shows better results, when all simulation data is used for calibration. However, if we restrict the simulation data used for calibration, the results for the reduced-form model deteriorate. We find the most reliable and stable results, when we make use of the functional dependence between recovery rates and default probabilities.