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This research aims to model the relationship between the credit risk signals in the credit default swap (CDS) market and agency credit ratings, and determines the factors that help explain the variation in such signals.

A comprehensive analysis of the differences in the relative credit risk assessments of CDS-based risk signals and agency ratings is provided. It is shown that the divergence between credit risk signals in the CDS market and agency ratings is explained by factors which the rating agencies may consider differently than credit market participants.

The results suggest that agency credit ratings of relative riskiness of a reference entity do not always correspond with assessments by CDS spreads, as the price of risk is a function of additional macro and micro factors that can be explained using statistical analysis.

This research is unique in modeling the relationship between the credit risk assessments of the CDS market and the agency ratings, which to the best of the authors' knowledge has not been analyzed before in terms of their agreement and the level of discrepancy between them. This model can be used by investors in debt instruments that are not explicitly CDSs or which have illiquid CDS contracts, to replicate market-based, point-in-time credit risk signals. Based on both market-based and firm-specific factors in this model, the results can be used to augment through-the-cycle credit risk assessments, analyze issues surrounding the pricing of CDSs and examine the policies of credit rating agencies.

The purpose of this paper is to examine the informative power of rating agencies in the process of establishing sovereign risk, over a ten‐year period (1997‐2006).

First, following an earlier model, the concept of noise‐rater risk is introduced. Second, four panels were carried out to identify the most significant macro factors in determination of sovereign ratings, taking into account contemporaneous and lagged variables. The dependent variable is sovereign rating issued at the end of each year. Third, three kinds of errors committed by rating agencies when altering the sovereign ratings of emerging countries are defined.

Noise‐rater risk amplifies the chances of noise traders obtaining higher returns than arbitrators. The panels show that, with the exception of debt, all other factors are sample dependant, and that variables and samples leave ample space for subjective factors. Analysis of errors demonstrates that rating agencies appear to lose their focus/modus operandi/principles in times of crisis, and that they commit more errors immediately prior and after the onset of a financial crisis.

The paper argues for a cautious analysis of rating agency's informative power. Like any other stakeholder, rating agencies are influenced by cognitive limitations, erroneous beliefs, and the cost of acquiring and using information.

The paper uses behavioral finance methodologies to observe rating agencies and demonstrates, from its observations of sovereign ratings, that agencies tend to fail at times of financial turmoil, i.e. when they are most needed, by abandoning their “look at the future” principle.

The creditworthiness of corporates is most visible in credit ratings. This paper aims to present an alternative credit rating measure independently of credit rating agencies. The credit rating score (CRS) is based on the credit default swap (CDS) market trading.

A CRS is developed which is a linear function of logarithmized CDS spreads. This new CRS is the first one that is completely independent of the rating agency. The estimated ratings are compared with ratings provided by Fitch Ratings for 310 European and US non-financial corporates.

The empirical analysis shows that logarithmized CDS spreads and issuer credit ratings by agencies have a linear relationship. The new CRS provides market participants with an alternative risk assessment, which is solely based on market factors, and does not rely on credit rating analysts. The results indicate that our CRS is able to anticipate agency ratings in advance. Moreover, the analysis shows that the trading volume has only a limited influence in the anticipation of rating changes.

This study shows a new approach to measure the creditworthiness of firms by analyzing CDS spreads. This is highly relevant for regulation, firm monitoring and investors.

The purpose of the article is to explain the significance of key features of the SEC’s new rules for credit rating agencies. Those rules include three key items: they prohibit the influence of sales or marketing considerations on criteria development; they include guidance that preserves the ability of ratings to serve as relative rather than absolute measures of credit risk; and they require cross-sector consistency of rating symbols. When they were released the significance of the rules was under-appreciated because of other simultaneous regulatory announcements.

The approach is to consider how effectively the rules address their target issues. In doing so the article explores how the final rules evolved from their original proposed form and from the statutory specifications in the 2010 Dodd-Frank Act.

The new rules should promote the integrity of credit ratings in the future. They should be effective in reducing the influence of sales and marketing considerations on the development of rating criteria. In addition they should enhance rating integrity through superior cross-sector consistency in the meanings of rating symbols while allowing rating agencies to maintain their traditional emphasis on relative risk.

The authors are not aware of any similar work assessing the selected provisions of the new SEC rules for credit rating agencies.

This paper aims to analyse the similarities and differences in the methodologies adopted by corporate social responsibility (CSR) rating agencies.

The authors gather secondary and primary evidences of practices from selected agencies on the methodologies and criteria they rely upon to assess a firm’s CSR performance.

The authors find not only evidence of similarities in the methodologies adopted by the CSR rating agencies (e.g. the use of environment, social and governance themes, exclusion criteria, adoption of positive criteria, client/“customised” input, quantification) but also several elements of differences, namely, in terms of the thresholds for exclusion, transparent vs confidential approach, industry-specific ratings and weights for each dimension. Drawing from Sandberg et al.’s (2009) conceptualisations, the authors tentatively argue that this mixed picture may reflect competing organisational pressures to adopt a differentiation approach at the strategic and practical levels whilst recognising, and incorporating, the “globalising” tendencies of the CSR business at the terminological levels.

Although these data are based on a relatively small number of agencies, the findings and analysis convey some implications for users of CSR ratings and policymakers, particularly in light of the recent Paris 2016 Agreement on Climate Change and the increased emphasis on the monitoring of social, environmental and governance performance.

The authors contribute to the literature by highlighting how key intermediate rating organisations operationalise notions of CSR.

The aim of the paper is to study the degree of independence of customers' portfolio concentration measure from the pricing policy adopted by rating agencies.

The paper tests different measures of customers value (revenues or profits and customer lifetime value) and different concentration measure (top customer or Herfindahl‐Hirschman index) on the customers' portfolio of rating agencies in the time period 1999‐2008. Simulating different pricing models, the paper tests the sensitivity of these measures to discounted fees applied to best customers and identifies measures that are more and less sensitive to the discount applied.

Concentration measures that consider all the customers' portfolios and look at both cost and revenues related to the service on a multi‐period time horizon (CLV) are less sensitive to the discount policy respect to the others.

Results point out some opportunities related to apply more complete approaches defined by marketing science on the financial service industry in order to construct better measures for the economic independence. The paper works only with publicly available data and more details about the fee applied to each customer could increase the significance of the results achieved.

The paper contributes to the current debate on the economic independence of rating agencies stressing the opportunity of rethinking the measures on economic independence that are currently considered by supervisory authorities.

The paper is the first empirical application of standard marketing concepts of customers' concentration measure to the rating industry.

The paper studies the pricing policies adopted by ratings agencies.

A credit rating, as a single indicator on one consistent scale, is designed as an objective and comparable measure within a credit rating agency (CRA). While research focuses mainly on the comparability of ratings between agencies, this paper additionally questions empirically how CRAs meet their promise of providing a consistent assessment of credit risk for issuers within and between market segments of the same agency.

Exhaustive and robust regression analyses are run to assess the impact of market sectors and rating agencies on credit ratings. The examinations consider the rating level, as well as rating downgrades as a further measure of empirical credit risk. Data stems from a large global sample of Bloomberg ratings from 11 market sectors for the period 2010-2018.

The analyses show differing effects of sectors and agencies on issuer ratings and downgrade probabilities. Empirical results on credit ratings and rating downgrades can then be attributed to investment grade and non-investment grade ratings.

The paper contributes to current finance research and practice by examining the credit rating differences between sectors and agencies and providing assistance to investors and other stakeholders, as well as researchers, how issuers’ sector and rating agency affiliations act as relative metrics.

Both consumer and corporate credit ratings agencies played a major role in the US subprime mortgage crisis. Equifax, Experian, and TransUnion deployed a formalized scoring system to assess individuals in mortgage origination, mortgage pools then were assessed for securitization by Moody's, S&P, and Fitch relying on expert judgment aided by formal models. What can we learn about the limits of formalization from the crisis? We discuss five problems responsible for the rating failures – reactivity, endogeneity, learning, correlated outcomes, and conflict of interest – and compare the way consumer and corporate rating agencies tackled these difficulties. We conclude with some policy lessons.