Usage of ZPP Model in Credit Risk Prediction
Subject Areas : Financial engineering
elahe
kamali
1
(Department of Business Management, Central Tehran Branch, Islamic Azad university, Tehran, Iran)
mirfeiz
fallah
2
(Department of Business Management, Central Tehran Branch, Islamic Azad university, Tehran, Iran)
Farhad
hanifi
3
(Department of Business Management, Central Tehran Branch, Islamic Azad university, Tehran, Iran)
Keywords: Credit Risk, Probability of Default, ZPP, KMV,
Abstract :
Credit risk issues and methods for identifying and predicting it have been constantly evolving over the past few decades. 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 present study, we have Investigated two models of advanced credit risk models, so two samples were selected, namely companies with financial problems and companies with financial health, in each group probabilities of default are estimated by two models which are KMV and ZPP, and then we compared probabilities of default. We have concluded that the ZPP model has more predictive ability than the KMV model.This method is denoted the Zero-Price Probability or simply the ZPP model. The main focus is on the new simulation based approach rather than the older established models.
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