International Journal of Global Energy Markets and Finance
ISSN (Print): ISSN Pending ISSN (Online): ISSN Pending Website: http://www.sciepub.com/journal/ijgefm Editor-in-chief: Abdelkader Derbali
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International Journal of Global Energy Markets and Finance. 2018, 1(1), 21-25
DOI: 10.12691/ijgefm-1-1-4
Open AccessReview Article

How the Default Probability is Defined by the CreditRisk+Model?

Abdelkader Derbali1,

1Higher Institute of Management of Sousse, University of Sousse, Tunisia

Pub. Date: April 24, 2018

Cite this paper:
Abdelkader Derbali. How the Default Probability is Defined by the CreditRisk+Model?. International Journal of Global Energy Markets and Finance. 2018; 1(1):21-25. doi: 10.12691/ijgefm-1-1-4

Abstract

The aim of this paper is to investigate theoretically one of the current models of credit portfolio management. There are currently three types of models to consider the risk of credit portfolio: the structural models (Moody's KMV model and CreditMetrics model) also defined by the models of the value of the firm, reduced form models also defined by models with intensity models (the actuarial models) and the econometric models (the Macro-factors model). The development of the 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 explained by other factors. We developed this paper to explain the different characteristics of the CreditRisk+ models. The purpose of this model is to calculate the default probability of credit portfolio.

Keywords:
risk management credit risk default probability structural models KMV model CreditRisk+ credit portfolio view

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References:

[1]  Koyluoglu, H., and Hickman, A. (1998). Reconcilable differences, Risk, 11(10): 56-62.
 
[2]  Crouhy, M., Galai, D. and Mark, R. (2000). A comparative analysis of current credit risk models. Journal of Banking & Finance, (24): 59-117.
 
[3]  Hamisultane, H. (2008). Modèles de gestion du risque de crédit. Investment System R&D, Document n°1.