Footnote:
Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments June 23, 2020 erstellt
Description:
A framework for measuring and managing the risk of embedded options in non-traded credit is developed. For typical bank clients there is no market information related to their ability to pay (bond or CDS spreads) available. In this case a bank has to rely solely on statistical data to judge the credit quality of a borrower. To value a loan with embedded options like prepayment rights in this context, a model is proposed that combines a stochastic interest rate model with statistical information on default and recovery rates. Using this as the basis for evaluating the risk of embedded options in loans, it is shown how the concepts of credit risk management can be transferred to this framework after defining a suitable concept of risk. It turns out that this modeling approach combines the theories of derivatives pricing and credit risk modeling in the sense that derivatives pricing theory measures the costs for hedging optional components in loans while credit risk modeling measures the risk that these hedging costs turn out to be inadequate. This risk depends not only on the single loan's risk characteristics but also on the dependence structure and the granularity of the total loan portfolio