Calibration of PD term structures: to be Markov or not to be

A common discussion in credit risk modelling is the question of whether term structures of default probabilities can be satisfactorily modelled by Markov chain techniques. Christian Bluhm and Ludger Overbeck show that empirical multi-year default frequencies can be interpolated well by continuous-time Markov chains if the Markov chain is allowed to evolve with non-homogeneous behaviour in time

The probability of default (PD) for a client is a fundamental risk parameter in credit risk management. It is common practice to assign to every rating grade in a bank's master scale a one-year PD in line with regulatory requirements (see Basel Committee on Banking Supervision, 2004). Table A shows an example for default frequencies assigned to rating grades from Standard & Poor's (S&P).

Click Here To Download PDF

Only users who have a paid subscription or are part of a corporate subscription are able to print or copy content.

To access these options, along with all other subscription benefits, please contact or view our subscription options here:

You are currently unable to copy this content. Please contact to find out more.

Sorry, our subscription options are not loading right now

Please try again later. Get in touch with our customer services team if this issue persists.

New to View our subscription options

Credit risk & modelling – Special report 2021

This Risk special report provides an insight on the challenges facing banks in measuring and mitigating credit risk in the current environment, and the strategies they are deploying to adapt to a more stringent regulatory approach.

The wild world of credit models

The Covid-19 pandemic has induced a kind of schizophrenia in loan-loss models. When the pandemic hit, banks overprovisioned for credit losses on the assumption that the economy would head south. But when government stimulus packages put wads of cash in…

You need to sign in to use this feature. If you don’t have a account, please register for a trial.

Sign in
You are currently on corporate access.

To use this feature you will need an individual account. If you have one already please sign in.

Sign in.

Alternatively you can request an individual account here