Emna Damak - Academia.edu (original) (raw)

Papers by Emna Damak

Research paper thumbnail of Bank Credit Risk Rating Process: Is There a Difference Between Developed and Developing Country Banks?

International Journal of Financial Research, Feb 2, 2022

The purpose of this article is to study empirically the bank credit risk rating (BCRR) process ac... more The purpose of this article is to study empirically the bank credit risk rating (BCRR) process across country groups (developed countries "DdC" against developing countries "DgC") after the 2012 revision of their methodologies as a response to the global and European crisis. We use the S&P"s ratings of 231 banks from 36 EMENA countries which of 18 are developed. We made this comparison based on the CAMELS model with a proposed "S" to BCRR. We perform "ordered logit" regression for the rating classes and complete our analysis by "linear multiple" regression for the rating grades. The results show that the entire rating process, including the weight of components, the important factors and the relevant variables, of DdC banks differs partly from this of DgC. The intrinsic credit quality component of the rating has more weight for the allocation of rating grades of DdC banks and the environment supports component has more weight for those of DgC. Some important factors represented by relevant variables are specific to each bank group and others are the same for both groups, but with a difference in the influence on the rating assigned. Sovereign rating has become more relevant to define bank groups than the country level of development.

Research paper thumbnail of Bank Credit Risk Rating Process: Is There a Change With the 2007-09 Crisis?

International Journal of Financial Research, 2021

The purpose of this article is to study empirically the bank credit risk rating (BCRR) process ov... more The purpose of this article is to study empirically the bank credit risk rating (BCRR) process over time using 89 banks from 27 EMENA countries rated by S&P’s simultaneously before and after 2007-09 crises. We made this comparison based on the CAMELS model with a proposed ‘S’ to BCRR. We use "ordered logit" regression for the rating classes and we complete our analysis by “linear multiple” regression for the rating grades. The results show that the rating changes in 2012 are mainly a methodology revision consequence of the entire rating process changes, including the weight of components, the important factors and the relevant variables in order to take into account some of the lessons learned from this global crisis. They also show a consistence between the BCRR's revealed and practiced methodologies revised by the credit rating agencies (CRAs).

Research paper thumbnail of Bank Credit Risk Rating Process: Is There a Difference Between Agencies?

International Journal of Financial Research

The purpose of this article is to compare the bank credit risk rating (BCRR) process between cred... more The purpose of this article is to compare the bank credit risk rating (BCRR) process between credit rating agency (CRA) after the 2012 revision of their methodologies using 76 banks from 23 EMENA countries rated simultaneously by S&P's, Moody's and FitchRatings. We made this comparison based on the CAMELS model with a proposed 'S’ to BCRR. We use “ordered logit” regression for the rating classes and we complete our analysis by “linear multiple” regression for the rating grades. The results show that the BCRR processes are largely consistent between agencies but not aligned. Some differences appear in the important factors and relevant variables of the intrinsic credit quality component that manifest themselves in specific behaviors distinguishing one agency to another. The three agencies agree on the factors: Capital, Earnings, Liquidity and Supports and the most relevant support variable is the sovereign rating of the bank's country of establishment. The results als...

Research paper thumbnail of CAMELS Model With a Proposed ‘S’ for the Bank Credit Risk Rating

International Journal of Economics and Finance

The purpose of this article is to adopt the CAMELS model to the bank credit risk rating by using ... more The purpose of this article is to adopt the CAMELS model to the bank credit risk rating by using simple indicators from publicly available quantifiable information retrieval from their financial statements. Then, it is to test its empirical validation after completion of its revised methodology in 2012 as response to the sub-prime crisis using the rating ‘all-in’ of 128 banks rated by Moody’s of 29 EMENA countries. We use ‘ordered logit’ regression for the variable to explain the rating classes and the bootstrap resampling techniques to assess the stability degree of the best model selected with the information criteria’s AIC. Under this scheme, the explanatory powers measured by Pseudo R2 of the best model is 56.47%. The results show that the two components: intrinsic credit quality and the support of the environment measured respectively by CAMEL factors and the proposed ‘S’ factor determine well the ‘all-in’ ratings. The sovereign rating of the bank establishment country, the size...

Research paper thumbnail of CAMELS Model With a Proposed ‘S’ for the Bank Credit Risk Rating

International Journal of Economics and Finance, Aug 20, 2018

The purpose of this article is to adopt the CAMELS model to the bank credit risk rating by using ... more The purpose of this article is to adopt the CAMELS model to the bank credit risk rating by using simple indicators from publicly available quantifiable information retrieval from their financial statements. Then, it is to test its empirical validation after completion of its revised methodology in 2012 as response to the sub-prime crisis using the rating "all-in" of 128 banks rated by Moody"s of 29 EMENA countries. We use "ordered logit" regression for the variable to explain the rating classes and the bootstrap resampling techniques to assess the stability degree of the best model selected with the information criteria"s AIC. Under this scheme, the explanatory powers measured by Pseudo R2 of the best model is 56.47%. The results show that the two components: intrinsic credit quality and the support of the environment measured respectively by CAMEL factors and the proposed "S" factor determine well the "all-in" ratings. The sovereign rating of the bank establishment country, the size and the "stand-alone" rating of the bank are the most relevant variables.

Research paper thumbnail of Bank Credit Risk Rating Process: Is There a Difference Between Developed and Developing Country Banks?

International Journal of Financial Research, Feb 2, 2022

The purpose of this article is to study empirically the bank credit risk rating (BCRR) process ac... more The purpose of this article is to study empirically the bank credit risk rating (BCRR) process across country groups (developed countries "DdC" against developing countries "DgC") after the 2012 revision of their methodologies as a response to the global and European crisis. We use the S&P"s ratings of 231 banks from 36 EMENA countries which of 18 are developed. We made this comparison based on the CAMELS model with a proposed "S" to BCRR. We perform "ordered logit" regression for the rating classes and complete our analysis by "linear multiple" regression for the rating grades. The results show that the entire rating process, including the weight of components, the important factors and the relevant variables, of DdC banks differs partly from this of DgC. The intrinsic credit quality component of the rating has more weight for the allocation of rating grades of DdC banks and the environment supports component has more weight for those of DgC. Some important factors represented by relevant variables are specific to each bank group and others are the same for both groups, but with a difference in the influence on the rating assigned. Sovereign rating has become more relevant to define bank groups than the country level of development.

Research paper thumbnail of Bank Credit Risk Rating Process: Is There a Change With the 2007-09 Crisis?

International Journal of Financial Research, 2021

The purpose of this article is to study empirically the bank credit risk rating (BCRR) process ov... more The purpose of this article is to study empirically the bank credit risk rating (BCRR) process over time using 89 banks from 27 EMENA countries rated by S&P’s simultaneously before and after 2007-09 crises. We made this comparison based on the CAMELS model with a proposed ‘S’ to BCRR. We use "ordered logit" regression for the rating classes and we complete our analysis by “linear multiple” regression for the rating grades. The results show that the rating changes in 2012 are mainly a methodology revision consequence of the entire rating process changes, including the weight of components, the important factors and the relevant variables in order to take into account some of the lessons learned from this global crisis. They also show a consistence between the BCRR's revealed and practiced methodologies revised by the credit rating agencies (CRAs).

Research paper thumbnail of Bank Credit Risk Rating Process: Is There a Difference Between Agencies?

International Journal of Financial Research

The purpose of this article is to compare the bank credit risk rating (BCRR) process between cred... more The purpose of this article is to compare the bank credit risk rating (BCRR) process between credit rating agency (CRA) after the 2012 revision of their methodologies using 76 banks from 23 EMENA countries rated simultaneously by S&P's, Moody's and FitchRatings. We made this comparison based on the CAMELS model with a proposed 'S’ to BCRR. We use “ordered logit” regression for the rating classes and we complete our analysis by “linear multiple” regression for the rating grades. The results show that the BCRR processes are largely consistent between agencies but not aligned. Some differences appear in the important factors and relevant variables of the intrinsic credit quality component that manifest themselves in specific behaviors distinguishing one agency to another. The three agencies agree on the factors: Capital, Earnings, Liquidity and Supports and the most relevant support variable is the sovereign rating of the bank's country of establishment. The results als...

Research paper thumbnail of CAMELS Model With a Proposed ‘S’ for the Bank Credit Risk Rating

International Journal of Economics and Finance

The purpose of this article is to adopt the CAMELS model to the bank credit risk rating by using ... more The purpose of this article is to adopt the CAMELS model to the bank credit risk rating by using simple indicators from publicly available quantifiable information retrieval from their financial statements. Then, it is to test its empirical validation after completion of its revised methodology in 2012 as response to the sub-prime crisis using the rating ‘all-in’ of 128 banks rated by Moody’s of 29 EMENA countries. We use ‘ordered logit’ regression for the variable to explain the rating classes and the bootstrap resampling techniques to assess the stability degree of the best model selected with the information criteria’s AIC. Under this scheme, the explanatory powers measured by Pseudo R2 of the best model is 56.47%. The results show that the two components: intrinsic credit quality and the support of the environment measured respectively by CAMEL factors and the proposed ‘S’ factor determine well the ‘all-in’ ratings. The sovereign rating of the bank establishment country, the size...

Research paper thumbnail of CAMELS Model With a Proposed ‘S’ for the Bank Credit Risk Rating

International Journal of Economics and Finance, Aug 20, 2018

The purpose of this article is to adopt the CAMELS model to the bank credit risk rating by using ... more The purpose of this article is to adopt the CAMELS model to the bank credit risk rating by using simple indicators from publicly available quantifiable information retrieval from their financial statements. Then, it is to test its empirical validation after completion of its revised methodology in 2012 as response to the sub-prime crisis using the rating "all-in" of 128 banks rated by Moody"s of 29 EMENA countries. We use "ordered logit" regression for the variable to explain the rating classes and the bootstrap resampling techniques to assess the stability degree of the best model selected with the information criteria"s AIC. Under this scheme, the explanatory powers measured by Pseudo R2 of the best model is 56.47%. The results show that the two components: intrinsic credit quality and the support of the environment measured respectively by CAMEL factors and the proposed "S" factor determine well the "all-in" ratings. The sovereign rating of the bank establishment country, the size and the "stand-alone" rating of the bank are the most relevant variables.