The Effect of Solicitation and Independence on Corporate Bond Ratings

Abstract:   This comparison of solicited and independent bond rating agencies performance reveals that the ratings assigned by Moody's and Standard & Poor's are consistently lower than those assigned by Duff and Phelps and Fitch IBCA and are consistently higher than those assigned by MCM. While Moody's and S&P generally downgrade bond ratings sooner than Duff and Phelps and Fitch IBCA, the four major agencies upgrade at the same time. Moody's tends to have a higher upgrade magnitude than Duff and Phelps, but the downgrade magnitudes do not differ. MCM upgrades its ratings more quickly than either Moody's or S&P. The results give support to the timeliness and accuracy of ratings provided by the independent agencies.     

Do measures of systemic risk predict U.S. corporate bond default rates?

Using univariate and multivariate Mixed Data Sampling (MIDAS) and LASSO estimation methodologies, we explore whether the U.S. annual average corporate bond default rate can be predicted by 12 monthly systemic risk measures proposed in the literature. We find that nearly all of the systemic risk indicators have predictive power for the default rate. Granger causality tests based on multivariate mixed frequency VAR models further support this conclusion. On the basis of MIDAS models, we illustrate that five of these indicators are able to forecast out-of-sample the 2009 corporate default crisis. Using a LASSO multivariate model, it is further shown that the systemic risk indicators can forecast out-of-sample both the 2009 default rate and the default rates during the buildup before the crisis and in the aftermath of the crisis. Institution-specific and volatility systemic risk measures are the most relevant for modeling U.S. corporate bond default rates, with the Conditional VaR measure of Adrian and Brunnermeier (2016) exhibiting the best performance.     

Tempered stable structural model in pricing credit spread and credit default swap

In this paper, we explore the features of a structural credit risk model wherein the firm value is driven by normal tempered stable (NTS) process belonging to the larger class of Lévy processes. For the purpose of comparability, the calibration to the term structure of a corporate bond credit spread is conducted under both NTS structural model and Merton structural model. We find that NTS structural model provides better fit for all credit ratings than Merton structural model. However, it is noticed that probabilities of default derived from the calibration of the term structure of a bond credit spread might be overestimated since the bond credit spread could contain non-default components such as illiquidity risk or asymmetric tax treatment. Hence, considering CDS spread as a reflection of the pure credit risk for the reference entity, we calibrate it in order to obtain more reasonable probability of default and obtain valid results in calibration of the market CDS spread with NTS structural model.     

How did increased competition affect credit ratings?

The credit rating industry has historically been dominated by just two agencies, Moody's and Standard & Poor's, leading to long-standing legislative and regulatory calls for increased competition. The material entry of a third rating agency (Fitch) to the competitive landscape offers a unique experiment to empirically examine how increased competition affects the credit ratings market. What we find is relatively troubling. Specifically, we discover that increased competition from Fitch coincides with lower quality ratings from the incumbents: Rating levels went up, the correlation between ratings and market-implied yields fell, and the ability of ratings to predict default deteriorated. We offer several possible explanations for these findings that are linked to existing theories.     

The effect of unfunded pension liabilities on corporate bond ratings,default risk,and recovery rate

Unfunded pension liabilities lower ratings of non-senior secured bonds but do not affect ratings of senior secured bonds due to their higher seniority. Pension funding improvement (deterioration) is associated with bond rating upgrade (downgrade). Moreover, large unfunded liabilities increase bond default risk and reduce the recovery rate of bondholders after controlling for credit ratings, suggesting that bond ratings do not fully capture pension underfunding risk. Overall, our results highlight the important effects of unfunded pension obligations on bond ratings, default risk, and creditors’ payoff, and suggest that investors should look beyond bond ratings in making investment decisions.     

A Comparison of Bond Ratings from Moody's S&P and Fitch IBCA

Previous research has found that the bond market values the ratings of Moody's and Standard & Poor's. This paper extends earlier research by comparing the ratings of Moody's, Standard and Poor's, and Fitch IBCA. The authors examine a very large database with monthly observations of bonds and bond ratings over a five‐year time period. The analysis focuses on comparing rating levels, rating changes, and the impact of ratings on bond yields. The results show that firms with publicly available Fitch IBCA ratings have higher ratings from Moody's and S&P than firms without Fitch IBCA ratings. The typical firm releasing a Fitch IBCA rating has a lower yield (controlling for Moody's and S&P rating), a more stable rating, and is more likely to receive an upgrade. For split‐rated bonds (Moody's vs. S&P), Fitch IBCA serves as a tiebreaker. This evidence is consistent with the bond market valuing the ratings of all three raters—Moody's, Standard & Poor's, and Fitch IBCA.     

Mandated accounting changes and debt covenants: The case of oil and gas accounting

The relationships among mandated accounting changes, bond covenants and security prices has been the focus of several studies. These studies have provided mixed evidence on the existence of a bond covenant effect on security prices. This paper suggests that inconclusive prior results are a consequence of inappropriately measuring the default risk of debt. Using an option pricing framework, it is shown that the debt to equity alone is not an adequate measure of default risk. In particular, both the debt to equity ratio and the total risk of the firm are necessary to adequately model the bond covenant effects of an accounting change. These theoretical propositions are supported by the empirical analysis of the security market reaction to changes in oil and gas accounting.     

In search of climate distress risk

Using the Merton distance to default model we investigate whether a firm's climate risk affects its default (distress) risk. S&P 500 non-financial firms during 2010–2019 are analysed and we employ both corporate carbon footprints and climate risk disclosures in annual filings to measure climate risk. Our results show that climate risk has a negative impact on firms' distance to default. This impact is limited to the disclosure of transition risk in annual filings. In contrast, disclosures of physical or non-specific risk do not affect firm-level default risk, while the impact of corporate carbon footprints is inconsistent but insignificant in most models. We also find that the negative effect of climate transition risk on firms' distance to default is stronger for firms headquartered in states with carbon pricing (California and states covered by the Regional Greenhouse Gas Initiative) and temporarily strengthens because of the Paris Agreement in 2015. However, this ‘Paris’ effect is short-lived and fades away in subsequent years.     

Firm heterogeneity and credit risk diversification

This paper examines the impact of neglected heterogeneity on credit risk. We show that neglecting heterogeneity in firm returns and/or default thresholds leads to underestimation of expected losses (EL), and its effect on portfolio risk is ambiguous. Once EL is controlled for, the impact of neglecting parameter heterogeneity is complex and depends on the source and degree of heterogeneity. We show that ignoring differences in default thresholds results in overestimation of risk, while ignoring differences in return correlations yields ambiguous results. Our empirical application, designed to be typical and representative, combines both and shows that neglected heterogeneity results in overestimation of risk. Using a portfolio of U.S. firms we illustrate that heterogeneity in the default threshold or probability of default, measured for instance by a credit rating, is of first order importance in affecting the shape of the loss distribution: including ratings heterogeneity alone results in a 20% drop in loss volatility and a 40% drop in 99.9% VaR, the level to which the risk weights of the New Basel Accord are calibrated.     

An Empirical Investigation of CDS Spreads Using a Regime-Switching Default Risk Model

Default risk in equity returns can be measured by structural models of default. In this article we propose a credit warning signal (CWS) based on the Merton Default Risk (MDR) model and a Regime-Switching Default Risk (RSDR) model. The RSDR model is a generalization of the MDR model, comprises regime-switching asset distribution dynamics, and thus produces more realistic default probability estimates in cases of deteriorating credit quality. Alternatively, it reduces to the MDR model. Using a dataset of U.S. credit default swap (CDS) contracts around the 2007-8 crisis we construct rating-based indices to investigate the MDR and RSDR implied probabilities of default in relation to the market-observed CDS spreads. The proposed CWS measure indicates an increase in implied default probabilities several months ahead of notable increases in CDS spreads.     

Implicit government guarantees and credit ratings

Exploiting the first default of a state-owned enterprise (SOE) in China, we analyze the role of implicit government guarantees in credit ratings. We consider two causes of implicit government guarantees. First, we suggest a “too big to fail” effect by revealing positive associations between credit ratings and issuer size, number of employees and taxes paid. Second, we propose a “government link” effect by showing positive associations between credit ratings and an issuer's state ownership, indicators for SOEs and central SOEs. Importantly, after the first SOE default, both dimensions of implicit government guarantees are weakened when explaining credit rating variations. Extending to analyses of yield spreads, we find that debt pricing relies more on credit ratings after the default event, consistent with bond investors weighing credit ratings more with weakened beliefs in implicit government guarantees. Collectively, our study proposes two dimensions of implicit government guarantees in credit ratings and shows how the initial SOE default significantly changes the role of such guarantees in credit ratings.     

The Cross‐Section of Credit Risk Premia and Equity Returns

We explore the link between a firm's stock returns and credit risk using a simple insight from structural models following Merton ( 1974 ): risk premia on equity and credit instruments are related because all claims on assets must earn the same compensation per unit of risk. Consistent with theory, we find that firms' stock returns increase with credit risk premia estimated from CDS spreads. Credit risk premia contain information not captured by physical or risk‐neutral default probabilities alone. This sheds new light on the “distress puzzle”—the lack of a positive relation between equity returns and default probabilities—reported in previous studies.     

An Empirical Estimation of Default Risk of the UK Real Estate Companies

Based on the Black and Scholes (Black, F., and M. Scholes. (1973). The Pricing of Options and Corporate Liabilities, Journal of Political Economy 81, 637–659) and Merton (Merton, R. C. (1974). On the Pricing of Corporate Debt: The Risk Structure of Interest Rates, Journal of Finance 29, 449–470) (BSM) contingent claims model, and KMV Corporation framework, we estimate the distance to default and the “risk neutral” default probabilities for a sample of 112 real estate companies over the period 1980 to 2001. Our empirical results classifies failed and non-failed companies into Type I error, cases that the BSM-type model fails to predict default when it did occur, and Type II error where BSM-type model predicts default when it did not occur. We find that none of the companies belong to the category of Type I error. Type II error is observed in 12 out of 112 companies. These results support the theoretical underpinnings of the BSM-type structural model in that the two driving forces of default are high leverage and high asset volatility.     

The Basel Committee proposals for a new capital accord: implications for Italian banks

Following a few general considerations on the recently proposed revision of the Basel Agreement on capital adequacy, this paper focuses on the first pillar of the Basel Committee proposals, the handling of capital requirements for credit risk in the banking book. The Basel Committee envisages an approach alternatively based on external ratings or on internal rating systems for the determination of the minimum capital requirement related to bank loan portfolios. This approach supports a system of capital requirements that is more sensitive to credit risk. On the basis of specific assumptions, these requirements provide a measure of the value at risk (VaR) produced by models used by major international banks. We first address the impact of the standardised and (internal ratings-based) IRB foundation approach using general data on Italian banks loans' portfolios default rates. We then simulate the impact of the proposed new rules on the corporate loan portfolios of Italian banks, using the unique data set of mortality rates recently published by the Bank of Italy. Three main conclusions emerge from the analysis: (i) the standardised approach implicitly penalizes Italian banks in their interbank funding as their rating is generally below AA/Aa, (ii) the average default rate experienced by Italian banks is higher than the one implied in the benchmark risk weight (BRW) proposed by the Basel Committee for the IRB foundation approach, thereby potentially leading to an increase in the regulatory risk weights, and (iii) the risk-weight is based on an average asset correlation that is significantly higher than the one historically recorded within the Italian banks' corporate borrowers. These findings support the need for a significant revision of the basic inputs and assumptions of the Basel proposals. Finally, in relation to the conditions that allow the capital market to effectively discipline banks, we comment on the proposals advanced in relation to the third pillar of the new capital adequacy scheme.     

Validation of default probability models: A stress testing approach

This study aims to evaluate the techniques used for the validation of default probability (DP) models. By generating simulated stress data, we build ideal conditions to assess the adequacy of the metrics in different stress scenarios. In addition, we empirically analyze the evaluation metrics using the information on 30,686 delisted US public companies as a proxy of default. Using simulated data, we find that entropy based metrics such as measure M are more sensitive to changes in the characteristics of distributions of credit scores. The empirical sub-samples stress test data show that AUROC is the metric most sensitive to changes in market conditions, being followed by measure M. Our results can help risk managers to make rapid decisions regarding the validation of risk models in different scenarios.     

Explaining credit rating differences between Japanese and U.S. agencies

We compare credit ratings assigned to Japanese firms by the two leading U.S. rating agencies and the two leading Japanese agencies. Our goal is to investigate the complaint that the U.S. agencies Moody's and Standard and Poor's (S&P) ignore special corporate governance features of Japanese firms, i.e., keiretsu affiliation. We find that it is true that ratings of Japanese firms by the U.S. agencies are systematically lower than those assigned by Japanese raters. However, the reasons for the differences are not found to be related to keiretsu affiliation. Thus, we reject one of the prominent reasons for rating differences put forth by managers of Japanese firms. This leaves open the question of what drives the difference. The phenomenon is clearly consistent with more general home bias documented in previous work.     

Expected Default Probabilities in Structural Models: Empirical Evidence

We apply a set of structural models (Black and Cox 1976; Collin-Dufresne and Goldstein 2001; Ericsson and Reneby 1998; Leland and Toft 1996; Longstaff and Schwartz 1995; Merton 1974) to estimate expected default probabilities (EDPs) for a sample of failed and non-failed UK real estate companies. Results are generally consistent with models’ predictions and estimates of EDPs for different models are closely clustered. The results of z-scores and synthetic ratings misclassify 33% of the total sample in contrast to 8% misclassification by structural models. Further analysis of EDPs based on logistic regressions suggests the observed misclassification of the companies by structural models is due to special company management and/or regulatory circumstances rather than limitations of these models.      

The Relevance of Accounting Data in the Measurement of Credit Risk

Abstract

Option pricing theory provides a robust and theoretically sound framework for the measurement of credit risk. Assuming perfect market conditions, information relevant to the measurement of a firm’s credit risk is reflected in its equity price, with no role for accounting data. This hypothesis is tested using UK data and credit ratings as a proxy for credit risk. It is found that Merton’s distance-to-default measure is the most significant variable in the measurement of credit risk. However, it is also found that accounting variables are incrementally informative when added to a model that contains only the distance-to-default measure. The incremental informativeness of accounting data varies across industries and depends on firm size. Although it is found that the general level of credit risk depends on the state of the economy, there is no evidence to suggest that the incremental informativeness of the accounting variables depends upon macroeconomic conditions.     

“投资人付费”vs.“发行人付费”:谁的信用评级质量更高？

本文选择2011-2015年被中债资信覆盖的发债A股上市公司作为主要研究对象,比较了“投资人付费”与“发行人付费”模式下的评级质量高低。研究发现:(1)与“发行人付费”评级相比,采用“投资人付费”模式的中债资信所作评级显著更低。(2)与“发行人付费”评级相比,当采用“投资人付费”模式的中债资信所作评级越低时,发行人未来盈利能力越差、预期违约风险越高,投资者要求的风险补偿也越高,这表明“投资人付费”模式下的信用评级质量更高。(3)“发行人付费”模式的评级结果可以在一定程度上反映公司的内部私有信息,但由于同时存在独立性缺失问题,“发行人付费”模式的信用评级质量仍然不如“投资人付费”模式的信用评级质量,这说明独立性对于评级机构尤其重要。     

Do sovereign rating changes trigger spillover effects?

This paper examines whether changes in a particular country's sovereign ratings provided by Standard and Poor's and Moody's trigger a spillover effect on other countries. The analysis focuses on two sets of countries namely where there are trade links between the countries and where there are links between the financial markets of each country. The findings indicate that there are more significant results when the links in financial markets are analysed compared to trade links. Moreover, the results are dependent on which rating is under analysis, that is, Standard and Poor's Local Currency, Standard and Poor's Foreign Currency, Moody's Bank Deposit or Moody's bonds and notes. Finally, there does appear to be a contamination effect for both upgrades and downgrades among the countries.