Credit Risk Predictive Ability of G-ZPP Model Versus V-ZPP Model

Credit risk management is becoming more and more important in recent years. When a company deals with a financial problem, it may not be able to fulfill its financial obligations, which can cause direct and indirect financial losses to shareholders, creditors, investors and other people in the community. Advanced credit risk models that are based on market value include improving credit quality as well as reducing or decreasing credit ratings. In the current study, we investigate a new model called ZPP that was introduced in ۲۰۰۷. This model is one of the advanced models of credit risk and the standard deviation of the model is calculated the GARCH model.  In this survey we test the accuracy of the ZPP model with GARCH and Simple Standard Deviation. In order to test the accuracy of the model, we have chosen two models: firms with financial problems and companies with financial health, and in each group, we estimated the probability of default by two models and then compared the probability of default with each other. Finally, we found the predictive ability of the G-ZPP model which was obtained by the GARCH model was better than the Variance-ZPP model.

Keywords:

ZPP , credit risk , Probability of Default , Monte-Carlo simulation