Evaluation of portfolio credit risk based on survival analysis for progressive censored data

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In credit risk management, the Basel committee provides a choice of three approaches to the financial institutions for calculating the required capital: the standardized approach, the Internal Ratings-Based (IRB) approach, and the Advanced IRB approach. The IRB approach is usually preferred compared to the standard approach due to its higher accuracy and lower capital charges. This paper use several parametric models (Exponential, log-normal, Gamma, Weibull, Log-logistic, Gompertz) to evaluate the credit risk of the corporate portfolio in the Jordanian banks based on the monthly sample collected from January 2010 to December 2015. The best model is selected using several goodness-of-fit criteria (MSE, AIC, BIC). The results indicate that the Gompertz distribution is the best model parametric model for the data.

Original languageEnglish
Title of host publication4th International Conference on Mathematical Sciences - Mathematical Sciences
Subtitle of host publicationChampioning the Way in a Problem Based and Data Driven Society, ICMS 2016
PublisherAmerican Institute of Physics Inc.
Volume1830
ISBN (Electronic)9780735414983
DOIs
Publication statusPublished - 27 Apr 2017
Event4th International Conference on Mathematical Sciences - Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society, ICMS 2016 - Putrajaya, Malaysia
Duration: 15 Nov 201617 Nov 2016

Other

Other4th International Conference on Mathematical Sciences - Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society, ICMS 2016
CountryMalaysia
CityPutrajaya
Period15/11/1617/11/16

Fingerprint

ratings
evaluation
risk management
goodness of fit
logistics

ASJC Scopus subject areas

  • Physics and Astronomy(all)

Cite this

Jaber, J. J., Ismail, N., & Mohd Ramli, S. N. (2017). Evaluation of portfolio credit risk based on survival analysis for progressive censored data. In 4th International Conference on Mathematical Sciences - Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society, ICMS 2016 (Vol. 1830). [040001] American Institute of Physics Inc.. https://doi.org/10.1063/1.4980929

Evaluation of portfolio credit risk based on survival analysis for progressive censored data. / Jaber, Jamil J.; Ismail, Noriszura; Mohd Ramli, Siti Norafidah.

4th International Conference on Mathematical Sciences - Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society, ICMS 2016. Vol. 1830 American Institute of Physics Inc., 2017. 040001.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Jaber, JJ, Ismail, N & Mohd Ramli, SN 2017, Evaluation of portfolio credit risk based on survival analysis for progressive censored data. in 4th International Conference on Mathematical Sciences - Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society, ICMS 2016. vol. 1830, 040001, American Institute of Physics Inc., 4th International Conference on Mathematical Sciences - Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society, ICMS 2016, Putrajaya, Malaysia, 15/11/16. https://doi.org/10.1063/1.4980929
Jaber JJ, Ismail N, Mohd Ramli SN. Evaluation of portfolio credit risk based on survival analysis for progressive censored data. In 4th International Conference on Mathematical Sciences - Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society, ICMS 2016. Vol. 1830. American Institute of Physics Inc. 2017. 040001 https://doi.org/10.1063/1.4980929
Jaber, Jamil J. ; Ismail, Noriszura ; Mohd Ramli, Siti Norafidah. / Evaluation of portfolio credit risk based on survival analysis for progressive censored data. 4th International Conference on Mathematical Sciences - Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society, ICMS 2016. Vol. 1830 American Institute of Physics Inc., 2017.
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