scholarly journals Bank Credit Risk Rating Process: Is There a Change With the 2007-09 Crisis?

2021 ◽  
Vol 12 (5) ◽  
pp. 41
Author(s):  
Emna Damak
Keyword(s):  
Credit Risk ◽  
Credit Rating ◽  
Lessons Learned ◽  
Bank Credit ◽  
Rating Agencies ◽  
Risk Rating ◽  
Rating Process ◽  
Before And After ◽  
Relevant Variables ◽  
Rating Changes

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).

scholarly journals Bank Credit Risk Rating Process: Is There a Difference Between Agencies?

2021 ◽  
Vol 12 (5) ◽  
pp. 194
Author(s):  
Emna Damak
Keyword(s):  
Credit Risk ◽  
Multiple Regression ◽  
Credit Rating ◽  
Bank Credit ◽  
Credit Rating Agency ◽  
Credit Quality ◽  
Logit Regression ◽  
Risk Rating ◽  
Rating Process ◽  
Relevant Variables

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 also confirm a consistence between the BCRR's revealed and practiced methodologies revised by the CRA.

scholarly journals CAMELS Model With a Proposed ‘S’ for the Bank Credit Risk Rating

2018 ◽  
Vol 10 (9) ◽  
pp. 69
Author(s):  
Emna Damak
Keyword(s):  
Credit Risk ◽  
Financial Statements ◽  
Bank Credit ◽  
Bootstrap Resampling ◽  
Logit Regression ◽  
Risk Rating ◽  
S Factor ◽  
Relevant Variables ◽  
Factor Determine ◽  
The Stability

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.

Bank Credit Risk Analysis and Bank Credit Rating

2020 ◽  
pp. 275-348
Author(s):  
Terence M. Yhip ◽  
Bijan M. D. Alagheband
Keyword(s):  
Risk Analysis ◽  
Credit Risk ◽  
Credit Rating ◽  
Bank Credit ◽  
Credit Risk Analysis

scholarly journals Credit Rating Changes and Subordinated Bond Spread: Evidence from China

2015 ◽  
Vol 2 (1) ◽  
pp. 1
Author(s):  
Robin Hang Luo ◽  
Jiaji Hao
Keyword(s):  
Credit Rating ◽  
Informational Content ◽  
Credit Rating Agencies ◽  
Sample Period ◽  
Bond Rating ◽  
Rating Agencies ◽  
Rating Changes ◽  
Statistical Results

We examine the bond spread reaction to subordinated bond rating changes during the sample period of 2006 to 2011 and find that bond spread reacted positively to downgrades, big in magnitude, but not statistically significant. The bond spread reaction to upgrades, however, was mixed and statistically insignificant, and small in magnitude. We conjecture that the insignificant statistical results regarding the effect of rating changes may be due to the lack of informational content of the ratings assigned to the subordinated bonds by Chinese credit rating agencies (CRAs). 

Part II The Financial Crisis of 2007–2011, 6 Market and Regulatory Failure

2018 ◽  
Author(s):  
Mccormick Roger ◽  
Stears Chris
Keyword(s):  
Risk Management ◽  
Financial Crisis ◽  
Credit Risk ◽  
Financial Market ◽  
Credit Rating ◽  
Third Party ◽  
Credit Rating Agencies ◽  
Rating Agencies ◽  
Market Participants ◽  
Regulatory Failure

This chapter first discusses the origins of the financial crisis, highlighting practice of ‘packaging and selling’ credit risk by financial market participants that led up to the crisis. It argues that although, in retrospect, many aspects of that practice look very bad indeed, the idea that banks might originate a credit exposure and then transfer the credit risk attached to it to a third party was, before the financial crisis, considered to be part and parcel of sound risk management. The discussion then turns to credit-rating agencies. Analysis of the financial crisis and ‘what went wrong’ has shown that rating agencies were too generous with their rating of many of the structured products that contributed to the collapse.

scholarly journals Oczekiwanie zmiany nastawienia credit ratings banków a kursy akcji przy uwzględnieniu poziomu rozwoju gospodarczego kraju

2017 ◽  
pp. 105-120
Author(s):  
Patrycja Chodnicka-Jaworska
Keyword(s):  
Credit Rating ◽  
Developing Economies ◽  
Credit Ratings ◽  
Bank Credit ◽  
Rates Of Return ◽  
Share Prices ◽  
Rating Agencies ◽  
Thomson Reuters ◽  
Event Study Method ◽  
Independent Variable

The aim of the paper is verification of the following hypothesis the share prices of banks have stronger reaction to bank credit rating announcements changes for a downgrade, both in developed and developing economies. The analysis(event study method) has been based on data from Thomson Reuters for the years 1980-2015 for 24 countries. Outlooks and watch lists proposed by all credit rating agencies have been used as an independent variable. Daily differences between the logarithmized rates of return of banks' shares have been used as dependent variable.

scholarly journals Empirical evolution of credit risk over a decade in IBEX. 35 companies and its relationship with the qualification of its ratings

2020 ◽  
Vol 16 (2) ◽  
pp. 61
Author(s):  
Josep Patau
Keyword(s):  
Credit Risk ◽  
Credit Rating ◽  
Clear Correlation ◽  
Crisis Period ◽  
Rating Agencies ◽  
Credit Rating Agency ◽  
Rating Agency ◽  
Determining Factors ◽  
Commercial Loans ◽  
The One

Object: The present work responds to two objectives. On the one hand, it describes the evolution of the main economic-financial indicators that influence credit risk (insolvency) for a sample of 10 Spanish companies listed on the IBEX 35. This analysis is studied for a comparative period of 10 years, which coincides with a pre-crisis stage (2002-2005) and an economic post-crisis phase (2012-2015). On the other hand, it corroborates the relationship between the analysed insolvency and the rating or credit-risk rating published for these companies by an internationally recognized credit rating agency, Standard & Poor's (S & P).Design / methodology: A sample of 10 companies and a 10-year period including the years 2002-2005 (pre-crisis) and the years 2012-2015 (post-crisis) are chosen, omitting the Spanish economic crisis that occurred in the year 2008. For the study of its evolution, 6 ratios obtained from the scientific literature that relate to credit risk and its effects on investments and company results are calculated. Finally, the correlations of these variables with the ratings of credit risk assessment by the rating agency S & P are measured. Descriptive statistics will assign value and graphics to this ten-year evolution, and with the incorporation of a factorial analysis, the correlation between the ratios and the S & P rating will be determined. The statistical analysis explains this correlation to a greater extent.Contributions / results: The results show a clear increase in the value of the impairment variable due to credit risk ten years later that directly affects the results of the companies, despite these companies having significantly reduced their investments in commercial loans pending collection and drastically reduced the period means of collection of clients. In turn, there is a clear correlation between the insolvency studied and the variables used by the S & P rating agency for the assessment of credit risk.Added value / conclusions: The empirical study concludes that there is a correspondence between insolvency and the rating given by an internationally prestigious rating agency (S & P) for the sample of 10 companies studied. Three variables – customer balance-accounts receivable, investments and the net amount of turnover – are determining factors explaining this correlation, and these three variables are the same ones that decisively influence both the pre-crisis period and the post-crisis period 10 years apart. The rating agencies weigh the insolvency variable in their analyses.

scholarly journals Dynamic Mapping of Probability of Default and Credit Ratings of Russian Banks

2020 ◽  
Vol 14 (4) ◽  
pp. 31-46
Author(s):  
Ella Khromova
Keyword(s):  
Credit Risk ◽  
Credit Rating ◽  
Credit Ratings ◽  
Quantitative Measure ◽  
Optimal Time ◽  
Investment Horizon ◽  
Investment Strategies ◽  
Probability Of Default ◽  
Rating Agencies ◽  
Dynamic Mapping

Investors are interested in a quantitative measure of banks’ credit risk. This paper maps the credit ratings of Russian banks to default probabilities for different time horizons by constructing an empirical dynamic calibration scale. As such, we construct a dynamic scale of credit risk calibration to the probability of default (PD).Our study is based on a random sample of 395 Russian banks (86 of which defaulted) for the period of 2007-2017. The scale proposed by this paper has three features which distinguish it from existing scales: dynamic nature (quarterly probability of default estimates), compatibility with all rating agencies (base scale credit ratings), and a focus on Russian banks.Our results indicate that banks with high ratings are more stable just after the rating assignment, while a speculative bank’s probability of default decreases over time. Hence, we conclude that investors should account for not only the current rating grade of a bank, but also how long ago it was assigned. As a result, a rising capital strategy was formulated: the better a bank’s credit rating, the shorter the investment horizon should be and the closer the date of investment should be to the rating assignment date in order to minimise credit risk.The scientific novelty of this paper arises from the process of calibration of a rating grade to dynamic PD in order to evaluate the optimal time horizon of investments into a bank in each rating class. In practical terms, investors may use this scale not only to obtain a desired credit rating, but also to identify quantitative measure of credit risk, which will help to plan investment strategies and to calculate expected losses.

The Regulatory Role of Credit Ratings and Voluntary Disclosure

2021 ◽  
Author(s):  
Riddha Basu ◽  
James P. Naughton ◽  
Clare Wang
Keyword(s):  
Voluntary Disclosure ◽  
Credit Rating ◽  
Credit Ratings ◽  
Regulatory Role ◽  
Rating Agencies ◽  
Corporate Credit ◽  
Quasi Experimental ◽  
Rating Changes ◽  
Corporate Credit Rating

We find that corporate credit rating changes have an effect on firms' voluntary disclosure behavior that is independent of the information they convey about firm fundamentals. Our analyses exploit two separate quasi-experimental settings that generate either exogenous credit rating downgrades or credit rating upgrades (i.e., credit rating label changes). We find evidence of a negative relation between the direction of the credit rating label change and the provision of voluntary disclosure in both settings-firms respond to exogenous downgrades by increasing voluntary disclosure and to exogenous upgrades by decreasing voluntary disclosure. The effects we document are attributable to the regulatory role rather than the information role of credit ratings. Overall, our analyses indicate that credit rating agencies as gatekeepers influence firms' provision of voluntary disclosure.

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