scholarly journals Corporate Yields: Effect of Credit Ratings and Sovereign Yields

2020 ◽  
Vol 110 ◽  
pp. 499-503
Author(s):  
Julia Bevilaqua ◽  
Galina Hale ◽  
Eric Tallman
Keyword(s):  
Credit Ratings ◽  
Corporate Bonds ◽  
Public Information ◽  
Corporate Bond ◽  
Bond Yields ◽  
Upward Trend ◽  
Bond Ratings ◽  
Rating Agencies ◽  
Advanced Economies ◽  
Over Time

We empirically evaluate the importance of two sources of public information affecting pricing of global corporate bonds: bond ratings provided by rating agencies and sovereign yields of the issuer's country. We find that both in the cross section of firms and over time more variation in corporate bond yields is explained by sovereign yields than by corporate bond ratings. When sovereign yields are high, their importance in pricing corporate bonds declines. In these states, for advanced economies' borrowers, the importance of corporate ratings increases. There is a small upward trend in the importance of corporate ratings over time.

scholarly journals Does CEO tenure influence corporate bond rating properties?

2015 ◽  
Author(s):  
◽  
Xia Zhang
Keyword(s):  
Information Sharing ◽  
Private Information ◽  
Credit Ratings ◽  
Public Information ◽  
Strategic Communication ◽  
Corporate Bond ◽  
Bond Rating ◽  
Rating Agencies ◽  
Ceo Tenure ◽  
The Impact

This study examines whether and how corporate bond rating quality varies with CEO tenure. Due to the expansive roles of credit ratings in capital market, managers have incentives to maintain or improve their ratings. Accumulated firm experience makes longer-tenured CEOs better at strategic communication with rating agencies and thereby more able to achieve the desired rating outcomes, leading to lower rating quality. Consistent with this prediction, I find that ratings are less accurate, less timely, and more volatile for issuers with longer-tenured CEOs. All these results hold after controlling for the impact of CEO tenure through public information sharing, suggesting that longer-tenured CEOs manage credit ratings through private information sharing with rating agencies. Moreover, investors do not understand such rating management by longer-tenured CEOs.

scholarly journals Can the dual-rating regulation improve the rating quality of Chinese corporate bonds?

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0259759
Author(s):  
Xiangyun Zhou
Keyword(s):  
Corporate Bonds ◽  
Corporate Bond ◽  
Logit Models ◽  
Bond Ratings ◽  
Rating Agencies ◽  
Different Types ◽  
Empirical Tests ◽  
Regulatory Effects ◽  
Reputation Effect

We developed a dual-reputational rating shopping model to introduce public and institutional reputations. Investor’s and regulator’s penalty rates are described as public and institutional reputations, respectively. We achieved the available conditions of single-rating and dual-rating regulations to prevent rating inflation in this model. To examine the regulatory effects of different types of regulations on Chinese corporate bond ratings, we utilize panel ordered logit models. Theoretical analysis and empirical tests show that, when the reputation effect is low, the single-rating regulation is better at improving rating quality, and when the reputation effect is high, the dual-rating regulation induces rating agencies to provide more accurate ratings. Compared to the regulatory effects of the single-rating and the multi-rating regulations, the dual-rating regulation most effectively improves the rating quality of corporate bonds and prevents rating inflation.

scholarly journals Determinants of Bond Rating and its Implications to Corporate Bond Yield

2019 ◽  
Vol 9 (2) ◽  
pp. 195-200
Keyword(s):  
Logistic Regression ◽  
Panel Data ◽  
Corporate Bonds ◽  
Corporate Bond ◽  
Company Size ◽  
Bond Yields ◽  
Bond Ratings ◽  
Bond Rating ◽  
Panel Data Regression ◽  
Data Regression

Identifying the factors that affect bond ratings is important in relation to investment decisions in long-term debt securities because they have an impact on corporate bonds. The research objective is to analyze the factors that influence bond ratings and their implications for corporate bond yields, both partially and simultaneously. This study uses a logistic regression model to estimate the determinants of corporate bond ratings and a panel data regression model to estimate the implications for corporate bond yields, by taking samples of corporate bonds listed on the Indonesia Stock Exchange (IDX) during the 2012-2016 period with a number of samples research with as many as 36 corporate bonds. Based on the results of the study, using the logistic regression method, the following research findings were obtained: company size, liquidity, leverage and profitability simultaneously affected bond ratings with a contribution of 33.62% (R2 ). In addition, the size and liquidity of the company have a positive and significant effect on bond ratings. While the results of the panel data regression analysis, it was found that company size, liquidity, leverage, profitability and bond rating simultaneously affected bond yields with a contribution of 70.4% (R2) while 29.6% was influenced by other variables. In addition, the size and leverage of the company has a negative and significant effect on the yield of corporate bonds. This study also shows that the larger the size of the company, the less sensitive the changes in bond yields and vice versa, the smaller the size of the company, the more sensitive it is to changes in corporate bond yields.

scholarly journals Does the Financial Status of Company Affect the Bond Credit Rating? ——Empirical Evidence from China's Shanghai and Shenzhen Stock Exchanges

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Yuyan Cai
Keyword(s):  
Credit Rating ◽  
Credit Ratings ◽  
Corporate Bonds ◽  
Principal Component ◽  
Corporate Bond ◽  
Stock Exchanges ◽  
Analysis Method ◽  
Financial Status ◽  
Financial Variables ◽  
The Impact

This article takes the companies that publicly issued corporate bonds on the Shanghai and Shenzhen Stock Exchanges from 2006 to 2018 as the research objects selecting six aspects that comprehensively reflect the 17 financial variables in 6 aspects: profitability, operating ability, bond repayment ability, development ability, cash flow and market value of the company. Principal component analysis method and factor analysis method are used to extract the principal factors of these financial indicator variables. That is how an ordered multi-classification Logistic regression model is constructed to test the impact of the Shanghai and Shenzhen Stock Exchanges’ financial status on the corporate bond credit rating. It turns out that the financial status of the Shanghai and Shenzhen Stock Exchanges have an important impact on the credit rating of corporate bonds. The financial status has a greater impact on corporate bonds with credit ratings of A- and AA-, while it has a smaller impact on corporate bonds with credit ratings above AA. The results of this article can help individual and institutional investors prevent risks from investing.

scholarly journals Bond Ratings And Their Determinants In A Changing Environment

2011 ◽  
Vol 9 (1) ◽  
pp. 132 ◽  
Author(s):  
Christina Ho ◽  
Ramesh P. Rao
Keyword(s):  
Changing Environment ◽  
Bond Ratings ◽  
Bond Rating ◽  
Rating Agencies ◽  
Stable Period ◽  
Over Time ◽  
Bond Rating Agencies

This study finds that bond rating agencies, to the extent that their behavior is captured in statistical rating models, tend to emphasize different variables over time and that this appears to be systematically related to the economic macro-environment. Specifically, the study finds that bond ratings are more sensitive to various measures of cashflow stability and solvency in an economically unstable period relative to a more stable period.

Corporate Bond Markets

2019 ◽  
pp. 113-130
Author(s):  
Kelly E. Carter
Keyword(s):  
Interest Rates ◽  
Credit Ratings ◽  
Corporate Bonds ◽  
Corporate Bond ◽  
Bond Markets ◽  
Bond Prices ◽  
Wall Street ◽  
Yield Curves ◽  
Bond Portfolios ◽  
The Impact

This chapter covers the fundamentals of corporate bond markets. It begins by highlighting the size and importance of these markets, followed by a discussion of the major types of corporate bonds and the process of issuing bonds. Next, the chapter provides a discussion of important relationships between a bond’s price and market interest rates, including the key observation that bond prices move opposite market interest rates. The next topic focuses on duration and convexity, which are techniques to estimate the dollar and percent changes in bond prices for a given change in market interest rates, followed by a discussion of bond immunization, which is a technique used to protect the value of bond portfolios from adverse changes in market interest rates. The final topics covered concern yield curves, credit ratings, and the impact of the Dodd-Frank Wall Street Reform Act of 2010 on corporate bond markets.

scholarly journals ESG Scores and the Credit Market

2020 ◽  
Vol 12 (8) ◽  
pp. 3456 ◽  
Author(s):  
Ga-Young Jang ◽  
Hyoung-Goo Kang ◽  
Ju-Yeong Lee ◽  
Kyounghun Bae
Keyword(s):  
Small Firms ◽  
Credit Rating ◽  
Credit Ratings ◽  
Debt Financing ◽  
Corporate Bond ◽  
Cost Of Debt ◽  
Rating Agencies ◽  
Bond Returns ◽  
The Cost ◽  
The Relationship

This study analyzes the relationship between Environmental, Social and Governance (ESG) scores and bond returns using the corporate bond data in Korea during the period of 2010 to 2015. We find that ESG scores include valuable information about the downside risk of firms. This effect is particularly salient for the firms with high information asymmetry such as small firms. Interestingly, of the three ESG criteria, only environmental scores show a significant impact on bond returns when interacted with the firm size, suggesting that high environmental scores lower the cost of debt financing for small firms. Finally, ESG is complementary to credit ratings in assessing credit quality as credit ratings cannot explain away ESG effects in predicting future bond returns. This result suggests that credit rating agencies should either integrate ESG scores into their current rating process or produce separate ESG scores which bond investors integrate with the existing credit ratings by themselves.

Credit Ratings and Rating Agencies

2020 ◽  
Author(s):  
Miles Livingston ◽  
Lei Zhou
Keyword(s):  
Credit Rating ◽  
Corporate Bonds ◽  
The United States ◽  
Corporate Bond ◽  
Insurance Companies ◽  
High Yield ◽  
Credit Rating Agencies ◽  
Probability Of Default ◽  
Rating Agencies ◽  
Bond Issues

Credit rating agencies have developed as an information intermediary in the credit market because there are very large numbers of bonds outstanding with many different features. The Securities Industry and Financial Markets Association reports over $20 trillion of corporate bonds, mortgaged-backed securities, and asset-backed securities in the United States. The vast size of the bond markets, the number of different bond issues, and the complexity of these securities result in a massive amount of information for potential investors to evaluate. The magnitude of the information creates the need for independent companies to provide objective evaluations of the ability of bond issuers to pay their contractually binding obligations. The result is credit rating agencies (CRAs), private companies that monitor debt securities/issuers and provide information to investors about the potential default risk of individual bond issues and issuing firms. Rating agencies provide ratings for many types of debt instruments including corporate bonds, debt instruments backed by assets such as mortgages (mortgage-backed securities), short-term debt of corporations, municipal government debt, and debt issued by central governments (sovereign bonds). The three largest rating agencies are Moody’s, Standard & Poor’s, and Fitch. These agencies provide ratings that are indicators of the relative probability of default. Bonds with the highest rating of AAA have very low probabilities of default and consequently the yields on these bonds are relatively low. As the ratings decline, the probability of default increases and the bond yields increase. Ratings are important to institutional investors such as insurance companies, pension funds, and mutual funds. These large investors are often restricted to purchasing exclusively or primarily bonds in the highest rating categories. Consequently, the highest ratings are usually called investment grade. The lower ratings are usually designated as high-yield or “junk bonds.” There is a controversy about the possibility of inflated ratings. Since issuers pay rating agencies for providing ratings, there may be an incentive for the rating agencies to provide inflated ratings in exchange for fees. In the U.S. corporate bond market, at least two and often three agencies provide ratings. Multiple ratings make it difficult for one rating agency to provide inflated ratings. Rating agencies are regulated by the Securities and Exchange Commission to ensure that agencies follow reasonable procedures.

The role of financial factors and non-financial factors on corporate bond and sukuk rating Indonesia

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nisful Laila ◽  
Sylva Alif Rusmita ◽  
Eko Fajar Cahyono ◽  
W.N.W. Azman-Saini
Keyword(s):  
Corporate Bonds ◽  
Corporate Bond ◽  
Ordinal Scale ◽  
Bond Ratings ◽  
Content Type ◽  
Leverage Ratio ◽  
Financial Factors ◽  
Maturity Date ◽  
Bond Issuers ◽  
Security Structure

Purpose This study aims to analyze the determinants of ratings of corporate bonds and sukuk issued by firms listed on the Indonesia Stock Exchange (IDX) for the 2013–2019 period. Design/methodology/approach This study uses a quantitative approach by testing hypotheses and using logistic regression. Ordinal logistic endogenous (or dependent) variables (Y) in ordinal logistics use data in the form of levels (ordinal scale). Independent (or exogenous) variables (X), include financial and non-financial factors for dependent (or endogenous) variables (Y), namely, of corporate bonds and sukuk ratings. There are two approaches to the study they are Logit and Gompit (Negative Log-Log. The population of the study is Indonesian companies listed on the IDX that issued bonds and sukuk for the 2013–2019 periods. The sampling technique is purposive. In total, 16 corporate companies adhering to the above criteria and issuing bonds and sukuk were chosen. In total, 270 types of bonds and 280 types of sukuk were selected as samples. Findings The results of the Logit and Gompit regression show that leverage ratio, firm size, security structure and maturity date are important determinants of corporate bond ratings while profitability and liquidity ratios appear to have no influence on the rating. In the case of sukuk, profitability, liquidity and maturity date play important roles in influencing the corporate sukuk rating. However, there is no evidence to suggest that leverage ratio, company size and security structure may affect sukuk ratings. Research limitations/implications For both sukuk and bond issuers, it is necessary to pay attention to the factors that may affect the ratings. Specifically, Sukuk issuers need to pay attention to the return of asset, current ratio, growth and structure. On the other hand, bond issuers need to consider depth to equity, structure and maturity. As for investors, the findings of this study reveal that both bond and sukuk ratings reflect their performance. Practical implications This study provides useful information for investors that allows them to assess the risk of sukuk or bonds chosen based on rating and financial performance. Originality/value The novelty of this study lies in its econometric methodology used to identify factors which influence sukuk and bond ratings. Specifically, this study used two different techniques that allow a robust conclusion to be drawn. Furthermore, this study provides a systematic analysis which allows comparison between factors which affect bond and sukuk ratings in Indonesia.

scholarly journals Rating Regulatory Mechanism Effect Promotion under the Environmental Issuance Effects: Based on the Incentive Difference Hotelling Model

2021 ◽  
Vol 13 (10) ◽  
pp. 5368
Author(s):  
Hanyi Zhao ◽  
Yixiang Tian ◽  
Xiangyun Zhou ◽  
Luping Zhang ◽  
Wei Meng
Keyword(s):  
Direct Effect ◽  
Indirect Effect ◽  
Corporate Bond ◽  
Regulatory Regime ◽  
Environmental Benefit ◽  
Bond Ratings ◽  
Hotelling Model ◽  
Rating Agencies ◽  
Regulatory Effects ◽  
Major Factors

Issuance effects are regarded as one of the most important aspects referring to the regulatory guidelines of green corporate bond ratings. This paper developed a new incentive difference Hotelling model, considering four major factors, i.e., the direct effect of issuance, the indirect effect of issuance, the reputation of rating agencies and the regulatory penalties. In this model, how the direct effect and the indirect effect impact the dual rating mechanism and the integrated rating mechanism was discussed. Numerical experiments were conducted to explore the regulatory effects on the two defined mechanisms in different situations. The results demonstrate that under each mechanism, the direct and indirect effects of issuance indirectly improve the effectiveness and efficiency of regulation by increasing the environmental benefit information content in the rating information, and the indirect effect has a greater impact. Moreover, it provides specific recommendations for the design of a regulatory regime. JEL: G18, G2.

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