ESG as a Measure of Credit Ratings

The aim of this study was to examine the impact of environmental, social, and governance (ESG) measures on credit ratings given to non-financial institutions by the largest credit rating agencies according to economic sector divisions. The hypotheses were as follows: a strong negative impact on non-financial institutions’ credit rating changes will result from ESG risk changes, and the reaction of credit rating changes will vary in different sectors. Panel event models were used to verify these hypotheses. The study used data from the Thomson Reuters Database for the period 2010–2020. The analysis was based on the literature on credit rating determinants and on papers and reports on COVID-19, ESG factors, and their impact on credit rating changes. Linear decomposition was used for the analysis. To verify these hypotheses, long-term issuer credit ratings presented by Moody’s and Fitch for European companies listed on these stock exchanges have been used. In the analyses, financial and non-financial factors were also considered. The results suggested that, within the last year, the methodology presented by credit rating agencies has changed, and ESG factors are one of the basic measures that are used to verify credit rating changes, especially those related to the pandemic.

Supply Chain Finance: Cost–Benefit Differentials under Reverse Factoring with Extended Payment Terms

This article studies the effects of reverse factoring in a supply chain when the buyer company facilitates its lower short-term borrowing rates to the supplier corporation in return for extended payment terms. We explore the role of interest rate changes, rating changes, and the business cycle position on the cost and benefit trade-off from a supplier perspective. We utilize a combined empirical approach consisting of an event study in Step 1 and a simulation model in Step 2. The event study identifies the quantitative magnitude of central bank decisions and rating changes on the interest rate differential. The simulation computes with a rolling-window methodology the daily cost and benefits of reverse factoring from 2010 to 2018 under the assumption of the efficient market hypothesis. Our major finding is that changes of crucial financial variables such as interest rates, ratings, or news alerts will turn former win–win into win–lose situations for the supplier contingent to the business cycle. Overall, our results exhibit sophisticated trade-offs under reverse factoring and consequently require a careful evaluation in managerial decisions.

Does Credit Rating Revisions Affect the Price of Common Stock: A Study of Indian Capital Market

The current investigation aims to assess the effect of credit assessment changes on the share prices of Indian companies from 2009 to 2019. The data of top 100 companies listed on National Stock Exchange (NSE) across 10 industries stem from CMIE databases. The excess stock return is compared with the market in a 15-day window around credit rating changes. The event effect on share prices is more in the pre-event window compared to the post-event window. Positive abnormal stock returns around upgrades through downgrades are statistically significant compared to upgrades. Credit ratings are not significant across industries, and agency nationality is a critical factor for calculating the intensity of price reaction.

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

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).

Detecting conflicts of interest in credit rating changes: a distribution dynamics approach

In this study, we compare the adjustments of credit ratings by an investor-paid credit rating agency (CRA), represented by Egan-Jones Ratings Company, and an issuer-paid CRA, represented by Moody’s Investors Service, vis-à-vis conflict of interest and reputation. A novel distribution dynamics approach is employed to compute the probability distribution and, hence, the downgrade and upgrade probabilities of a credit rating assigned by these two CRAs of different compensation systems based on the dataset of 750 U.S. issuers between 2011 and 2018, that is, after the passage of the Dodd–Frank Act. It is found that investor-paid ratings are more likely to be downgraded than issuer-paid ratings only in the lower rating grades, which is consistent with the argument that investor-paid agencies have harsher attitudes toward potentially defaulting issuers to protect their reputation. We do not find evidence that issuer-paid CRAs provide overly favorable treatments to issuers with threshold ratings, implying that reputation concerns and the Dodd–Frank regulation mitigate the conflict of interests, while issuer-paid CRAs are more concerned about providing accurate ratings.

The Regulatory Role of Credit Ratings and Voluntary Disclosure

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.

A Multi-Country Study of Factors Affecting Credit Ratings Revisions

This paper reveals findings from extending corporate credit rating studies towards (i) new ratings, affirmation, confirmation, watchlists, and withdrawal, which together represent five out of eight rating types yet to be studied rigorously (there are several papers on upgrades and downgrades); and (ii) identifying key firm-specific factors affecting stock prices around the rating revisions in markets not yet studied. The firmspecific factor effects are measured using the Ordered Probit methodology. Results show that investment and speculation grade issues have the most pronounced effects on price changes. Further findings are: interest-coverage, profitability and leverage ratios, all of which stand out as the most relevant firm-specific factors correlated with stock price changes. An interesting new finding is the discovery of corruption perception scores as a new measure is significantly influencing affirmation, confirmation and downgrade ratings. These new findings are likely to be of interest to investors, corporations wanting to know rating change effects and the external regulators concerned with financial weaknesses/strengths of listed firms facing rating changes.

Road infrastructure development under PPP model in India: a credit rating perspective

PurposeThe study analyzes significant parameters defining the credit worthiness, economic viability and managerial efficiency of special purpose vehicles (SPVs) of infrastructure development firms engaged in the execution of road projects under PPP model in India.Design/methodology/approachThe study is based on a comprehensive review of credit rating reports of major rating agencies. In particular, 18 special purpose vehicles (13 BOT-toll–based and 5 BOT-annuity–based road projects) during the period 2010–2019 were considered to conduct a comparative analysis of their rating progression. Considering both financial as well as nonfinancial parameters, their segregation was done on the basis of strengths, constraints and key rating sensitivities influencing the ratings of SPVs involved in road projects under PPP model.FindingsPromoters' credibility emerged as an important factor affecting PPP credit ratings. Other prominent factors included nature of stretch and regulatory terms and conditions and the project's potential to generate cash flows. Inability of PPP projects to generate the projected levels of toll collections was a major constraint and hampered ratings over time. Growth in traffic was a key sensitive area in a toll-based project. Interestingly, despite the fixed nature of revenues, BOT (annuity) projects were impacted by rating changes.Research limitations/implicationsFewer sample projects (for which the data were available) was a constraint. Future research could consider larger data sets to provide deeper insights. An examination of credit rating parameters using rating reports of projects in other developing nations could provide meaningful implications. The findings of this research however cannot be undermined as the study bridges a gap in existing literature pertaining to the examination of PPP model from a credit rating perspective.Practical implicationsThis study would guide project developers, government agencies and awarding agencies of PPP road projects to anticipate the challenges and take adequate steps to mitigate them.Originality/valueResearch in the area of PPP projects is skewed toward risk assessment with respect to financial parameters. The present study emphasizes the rating framework of SPVs. Comprehensive examination of factors affecting project ratings in the form of projects' strengths, constraints and sensitivities would provide inputs to academics and researchers.