Abstract:
The present paper aimed at studying the current models of credit portfolio management. There are currently three types of models which consider the risk of credit portfolio: the structural models (Moody's KMV model, and Credit- Metrics model), the intensity models (the actuarial models) and the econometric models (the Macro-factors model). The development of these three types of models is based on a theoretical basis developed by several researchers. The evolution of their default frequencies and the size of the loan portfolio are expressed as functions of macroeconomic and microeconomic conditions as well as unobservable credit risk factors, which would be explained by other factors. The present study developed three sections to explain the different characteristics of those three models. The purpose of all the models is to express the default probability of credit portfolio
Machine summary:
To protect itself against the risk which results from potential losses bound to the evolutions of the portfolio, Kealhofer, McQuown and Vasicek (1993) based on the determination of a random size L relative to the losses of the portfolio which is defined in a general way and on a horizon H as follows: ܰ ܺ 2 ൌ ܰሺെܦܦሻ L ൌ V െ V ୌ ୌ σ √T ୈ Then we can obtain the frequency planned by Where V ౄ ొీ indicates the value of the default (Expected Default Frequency: EDF) such as: EDF ൌ NሺെDDሻ However, the default probability does not correspond to the normal law.
Unlike the approaches developed by the other models of management of a portfolio of credit, the probability of default in Credit-Metrics is given by rating agencies for the big companies and by methods of scoring and mapping for small and medium-sized firms (Paleologo et al.
By continuing in the same context of analysis that is the use of the notation BBB as the example, the following table of the Forward rates can be used: It is supposed in this case which a noted transmitter BBB has emitted a Bond for 100 By basing itself on the formula above, being able to us determine the various possible values of fire of type BBB according to his possible migrations towards other notations (Crouhy et al.
The KMV model and Credit Portfolio View base their approach on the same empirical observation that default and migration probabilities vary over time.