With the forthcoming new regulations, IFRS9, financial institutions will be required to model life time expected credit losses. Consequently, it is necessary to model the term structure of default probabilities for different products/counter-parties. How can one successfully implement such a model?
In current literature one finds a variety of approaches to model the term structure of default probabilities. Most often, these approaches utilize market data to extract implied default probabilities over a certain horizon, for instance using bonds or credit default swaps. However, these methods are only applicable when such data is available. The term structure of default probabilities for non-listed enterprises (for instance) will be much more cumbersome to determine. Also, many models does not rigorously incorporate default correlations which is necessary for the application of a portfolio. Presumably one will only be able to use historical data of credit migrations.
In accordance with Bluhm and Overbeck (2007) one find the model credit migrations using Markov chains, and from there find each rating grades term structure.
Have anyone come across other interesting literature which allows one to model term structures of default probabilities only using historical credit migration data?