THE INFORMATIONAL CONTENT OF BOND RATINGS

This paper explores the risk structure of interest rates. The focus is on whether yields on industrial bonds indicate that market participants base their evaluations of a bond issue's default risk on agency ratings or on publicly available financial statistics. Using a non-linear least squares procedure, the yield-to-maturity is related to Moody's rating, Standard and Poor's (S&P) rating, and accounting measures of creditworthiness such as coverage and leverage. Market yields are found to be significantly correlated with both the ratings and a set of readily available financial accounting statistics. These results indicate (1) that market participants base their evaluations of an issue's creditworthiness on more than the agencies' ratings and (2) that the ratings bring some information to the market above and beyond that contained in the set of accounting variables. The paper also asks whether the market views Moody's and Standard and Poor's ratings as equally reliable measures of risk or whether the market attaches more weight to one agency's ratings than the other. Finally, the hypothesis that the market pays more attention to the accounting measures and less to the ratings if the rating has not been reviewed recently is tested.     

INFORMATION OPACITY AND FITCH BOND RATINGS

We examine the marginal impact of Fitch ratings on the at‐issuance yields of industrial and utility bonds rated by Moody's and Standard & Poor's. We find that Fitch ratings reduce the yield premiums on information‐opaque bonds by about 30%, or 15 basis points. The finding is robust even when a Fitch rating exactly equals the two major ratings or their average. The findings suggest that Fitch ratings are not redundant but bring additional information to investors. Increased competition in the rating industry enhances the information efficiency of the bond market, and the existence of smaller rating agencies is economically justified.     

SPLIT RATINGS,BOND YIELDS,AND UNDERWRITER SPREADS

A split bond rating occurs when Moody's and Standard & Poor give different ratings to the same issue. We examine 1,277 public industrial bond issues, where 221 have split ratings, issued from 1980 through mid-1993. For split-rated industrial bonds, neither rating agency consistently gives higher ratings. Earlier studies find yields for split-rated bonds to be priced as either the higher or the lower of the ratings. We find the yields on split-rated bonds to be an average of the yields on the two ratings. Split ratings for industrial bonds appear to reflect random differences on the part of rating agencies. Our results differ from previous studies because we use a substantially larger sample and include high-yield bonds. As long as a bond has an investment-grade rating, the underwriter fees are found to be essentially the same for all rating categories. Below investment grade, the rating substantially affects the underwriter fee. Thus, split ratings for high-yield bonds have an important effect on the underwriter spread.     

Moody's and S&P Ratings: Are They Equivalent? Conservative Ratings and Split Rated Bond Yields

We examine the relative impact of Moody's and S&P ratings on bond yields and find that at issuance, yields on split rated bonds with superior Moody's ratings are about 8 basis points lower than yields on split rated bonds with superior S&P ratings. This suggests that investors differentiate between the two ratings and assign more weight to the ratings from Moody’s, the more conservative rating agency. Moody's becomes more conservative after 1998 and the impact of a superior Moody's rating becomes stronger. Furthermore, the differential impact of the two ratings is more pronounced for the more opaque Rule 144A issues.     

Does it matter who pays for bond ratings? Historical evidence

We test whether Standard and Poor's (S&P) assigns higher bond ratings after it switches from investor-pay to issuer-pay fees in 1974. Using Moody's rating for the same bond as a benchmark, we find that when S&P charges investors and Moody's charges issuers, S&P's ratings are lower than Moody's. Once S&P adopts issuer-pay, its ratings increase and no longer differ from Moody's. More importantly, S&P only assigns higher ratings for bonds that are subject to greater conflicts of interest, measured by higher expected rating fees or lower credit quality. These findings suggest that the issuer-pay model leads to higher ratings.     

THE IMPACT OF SPLIT BOND RATINGS ON RISK PREMIA

Interest rates for bonds are negatively correlated with credit ratings assigned by agencies such as Moody's Investor Service and Standard & Poor's. Still in dispute is whether or not the ratings themselves convey information that is reflected in prices, hence interest rates in the bond markets. Disagreement between these two agencies' ratings leads to “split” ratings, and in this paper, the authors use the phenomenon of split ratings to assess whether or not ratings have a separate impact on bond prices. The results indicate that a downside split appears to have greater bond yield impact than an upside split. The findings are inconsistent with bond market efficiency, at least in the strong form. The market considers the quality of a split-rated bond to reflect the lower of the two ratings. Finally, the symmetry of the results with respect to the ratings agencies indicates that neither agency has more influence than the other in determining bond yields.     

Rating shopping and rating inflation in Israel

Firms may exploit the option of choosing among different rating agencies in order to pick the highest rating offered. This possibility, known as rating shopping, is relatively limited on the US corporate bond market because the two main rating agencies (S&P and Moody's) rate virtually all large bond issuers. In this study, we use the data on corporate bond ratings assigned by two Israeli rating agencies affiliated with S&P and Moody's during the period 2004–2012. We show that while one agency (Midroog) systematically assigned higher ratings, the ratings of the other agency (S&P-Maalot) were inflated due to rating shopping. However, despite the many features that encourage rating inflation, the resulting distortion was relatively small (one notch). This may be a fair price for maintaining a competitive rating industry.     

Combining Bond Rating Forecasts Using Logit

Companies sometimes use statistical analysis to anticipate their bond ratings or a change in the rating. However, different statistical models can yield different ratings forecasts, and there is no clear rule for which model is preferable. We use several forecasting methods to predict bond ratings in the transportation and industrial sectors listed by Moody's bond rating service. A variant of the ordered‐logit regression‐combining method of Kamstra and Kennedy 1998 yields statistically significant, quantitatively meaningful improvements over its competitors, with very little computational cost.     

PREDICTING INDUSTRIAL BOND RATINGS WITH A PROBIT MODEL AND FUNDS FLOW COMPONENTS

Since 1978, there has been a significant change in new bond offerings with a substantive increase in the number of nonconvertible high risk bonds. This study uses an n-chotomous multivariate probit model with cash-based funds flow components and financial ratios to predict industrial bond ratings. The n-chotomous probit model provides superior information for evaluating the bond classification process. The model determines the probabilities of a bond being rated in one of three risk classes. The distribution of the probabilities for each predicted bond rating provides a wealth of new information for evaluating the accuracy of the actual rating. New and reclassified bond ratings by Moody's in 1983 provide the information base for the model that is used to predict 1984 ratings. Initially the classification and predictive results were slightly lower than previous studies. A careful analysis of the probability distributions showed that results were close to being correct in over 90 percent of the cases. The analysis found five cash flow components to be significant in predicting the bond ratings of reclassified issues. The significant components were inventories, other current liabilities, dividends, long-term financing, and fixed coverage charges. The likelihood tests indicated that both ratios and funds flow components contributed information that significantly improved the ability of the n-chotomous multivariate probit model to classify new and revised bond ratings. The study provides valuable insight and nuances concerning the bond-rating process.     

INTRA-INDUSTRY EFFECTS OF BOND RATING ADJUSTMENTS

Several studies find that bond rating downgrades cause negative valuation effects. Other studies find that signals conveyed by earnings releases, earnings forecasts, bankruptcies, and stock offerings of individual firms can be transmitted to their corresponding industries. By combining the two sets of studies, we hypothesize that bond rating changes may contain relevant information not only about the firm, but also about the corresponding industry. We find significantly negative valuation effects for rating downgrades, which are transmitted throughout the industry. Furthermore, we find that intra-industry effects depend on particular characteristics of the bond downgrade, the downgraded firm, and industry rivals. Specifically, the negative intra-industry effects are more pronounced when (1) the downgraded firm experiences a more severe share price response to the bond rating downgrade, (2) the downgraded firm is dominant in the industry, (3) the downgraded firm is more closely related to its rivals in the industry, and (4) the downgrade is due to a deterioration in the firm's financial prospects.     

Moody’s investors service response to the consultative paper issued by the Basel Committee on Bank Supervision “A new capital adequacy framework”

Moody's endorses the Basel Committee's proposal to use banks' internal risk assessments to refine the Basel Accord's risk weights on bank assets and commitments. External risk assessments, such as Moody's credit ratings, will likely play a supporting role as direct inputs into banks' internal rating systems and as tools for benchmarking and validating those systems. However, the widespread use of ratings in regulation threatens to undermine the quality of credit over time by increasing rating shopping, decreasing rating agency independence, and reducing incentives to innovate and improve the quality of ratings. This paper discusses how bank regulators can use external ratings in ways that mitigate the adverse incentives created by the resulting regulatory demand for rating agency services.     

Do Rating Agencies Benefit from Providing Higher Ratings? Evidence from the Consequences of Municipal Bond Ratings Recalibration

We ask whether credit rating agencies receive higher fees and gain greater market share when they provide more favorable ratings. To investigate this question, we use the 2010 rating scale recalibration by Moody's and Fitch, which increased ratings absent any underlying change in issuer credit quality. Consistent with prior research, we find that the recalibration allowed the clients of Moody's and Fitch to receive better ratings and lower yields. We add to this evidence by showing that the recalibration also led to larger fees and to increases in the market shares of Moody's and Fitch. These results are consistent with critics’ concerns about the effects of the issuer‐pay model on the credit ratings market.     

Sovereign credit ratings during the COVID-19 pandemic

Using 603 sovereign rating actions by the three leading global rating agencies between January 2020 and March 2021, this paper shows that the severity of sovereign ratings actions is not directly affected by the intensity of the COVID-19 health crisis (proxied by case and mortality rates) but through a mechanism of its negative economic repercussions such as the economic outlook of a country and governments' response to the health crisis. Contrary to expectations, credit rating agencies pursued mostly a business-as-usual approach and reviewed sovereign ratings when they were due for regulatory purposes rather than in response to the rapid developments of the pandemic. Despite their limited reaction to the ongoing pandemic, sovereign rating news from S&P and Moody's still conveyed price-relevant information to the bond markets.     

Sovereign rating actions and the implied volatility of stock index options

This paper examines the interaction between the equity index option market and sovereign credit ratings. S&P and Moody's signals exhibit strong impact on option-implied volatility while Fitch's influence is less significant. Moody's downgrades reduce the market uncertainty over the rated countries' equity markets. Strong causal relationships are found between movements in the option-implied volatility and all credit signals released by S&P and Fitch, but only actual rating changes by Moody's, implying differences in rating agencies' policies. The presence of additional ratings tends to reduce market uncertainty. The findings highlight the importance of rating information in the price discovery process and offer policy implications.     

The information content of three credit ratings: the case of European residential mortgage-backed securities

We assess the information content of three credit ratings for tranches of newly issued European residential mortgage-backed securities. We find that tranches rated by three credit rating agencies where the rating by Standard & Poor's (S&P's) Ratings Service or Fitch is inferior to Moody's lead to higher funding costs and reflects what we refer to as rating risk. Our results suggest that market participants do not view credit ratings by Fitch and S&P's as redundant despite the fact that both employ the same rating approach.     

Do Bond Covenants Affect Borrowing Costs?

High yield bond investors spend a great deal of time studying covenants. They even hire specialized consultants to help them interpret the dense language of indentures. But for all that, does a company's decision to offer strong rather than weak covenants—or to offer covenants at all—have a measurable impact on its borrowing costs? There is surprisingly little evidence that variation in credit risk premiums reflects the presence or absence of covenants. Taking advantage of a newly available kind of data—Moody's Investors Service's Covenant Quality (CQ) ratings, which were initiated in 2011—the authors studied each newly issued U.S. high yield bond beginning in 2011 using Moody's CQ ratings, where a rating of “1” represents the strongest covenant rating and “5” the weakest. The authors hypothesize that if investors are willing to pay for covenant protection, bonds with weak CQ scores should have spreads that are higher, on average, than the medians of the bonds in their rating group. What they found, however, was that even bonds rated CQ5, indicating negligible protection, had spreads that were only 9.54 basis points higher than the median of companies with the same credit rating. The authors also found, contrary to their initial supposition, that higher yields were associated with stronger covenants, suggesting that investors demand more protection on issues they view as having greater credit risk than other equivalently rated issues.     

The ordered qualitative model for credit rating transitions

Information on the expected changes in credit quality of obligors is contained in credit migration matrices which trace out the movements of firms across ratings categories in a given period of time and in a given group of bond issuers. The rating matrices provided by Moody's, Standard & Poor's and Fitch became crucial inputs to many applications, including the assessment of risk on corporate credit portfolios (CreditVar) and credit derivatives pricing. We propose a factor probit model for modeling and prediction of credit rating matrices that are assumed to be stochastic and driven by a latent factor. The filtered latent factor path reveals the effect of the economic cycle on corporate credit ratings, and provides evidence in support of the PIT (point-in-time) rating philosophy. The factor probit model also yields the estimates of cross-sectional correlations in rating transitions that are documented empirically but not fully accounted for in the literature and in the regulatory rules established by the Basle Committee.     

THE DYNAMICS OF BOND YIELD SPREADS AROUND RATING REVISION DATES

We examine the effect of rating revisions on sterling Eurobond yields using a panel model with conditional heteroskedasticity that controls for event‐induced changes in the variance of spreads. Positive rating revisions are fully anticipated by the time the upgrade occurs. Negative revisions are only partially anticipated, and spreads on downgraded bonds rise for some time after the downgrade has been announced. This asymmetry is not apparent in a conventional event study model. All ratings announcements are accompanied by a temporary fall in yield volatility. We attribute this to the resolution of uncertainty about the true rating of the bond.     

Competition in the credit rating Industry: Benefits for investors and issuers

We empirically investigate the benefits of multiple ratings not only at issuance of debt instruments but also during the subsequent monitoring phase. Using a record of monthly credit rating migration data on all U.S. residential mortgage-backed securities rated by Standard & Poor's, Moody's, and Fitch between 1985 and 2012 (154,600 tranches), our results provide empirical evidence that rating agencies put more effort in rating and outlook revisions when tranches have assigned multiple ratings. Furthermore, we see that in the case of multiple ratings, agencies do a better job in discriminating tranches with respect to default risk. On the downside, we observe a shift in collateral towards senior tranches and incentives for issuers to engage in rating shopping activities, but find no evidence that rating agencies exploit such behavior to attract more rating business. Our results contribute to the literature on information production of credit ratings and extend the perspective to the monitoring period after issuance.     

Market-implied ratings and their divergence from credit ratings

In this article, we investigate the divergence between credit ratings (CRs) and Moody's market-implied ratings (MIRs). Our evidence shows that rating gaps provide incremental information to the market regarding issuers' default risk over CRs alone in the short horizon and outperform CRs over extended horizons. The predictive ability of rating gaps is greater for more opaque and volatile issuers. Such predictability was more pronounced during the 2008 financial crisis but weakened in the post–Dodd–Frank Act period. This finding is consistent with credit rating agencies’ efforts to improve their performance when facing regulatory pressure. Moreover, our analysis identifies rating-gap signals that do (do not) lead to subsequent Moody's actions to place issuers on negative outlook and watchlists. We find that negative signals from MIR gaps have a real economic impact on issuers’ fundamentals such as profitability, leverage, investment, and default risk, thus supporting the recovery-efforts hypothesis.