Do Firms Target Credit Ratings or Leverage Levels?

2009 ◽  
Vol 44 (6) ◽  
pp. 1323-1344 ◽  
Author(s):  
Darren J. Kisgen
Keyword(s):  
Capital Structure ◽  
Empirical Model ◽  
Credit Rating ◽  
Credit Ratings ◽  
Structure Activity ◽  
Commercial Paper ◽  
Net Equity ◽  
Target Leverage ◽  
Rating Downgrades

AbstractFirms reduce leverage following credit rating downgrades. In the year following a downgrade, downgraded firms issue approximately 1.5%–2.0% less net debt relative to net equity as a percentage of assets compared to other firms. This relationship persists within an empirical model of target leverage behavior. The effect of a downgrade is larger at downgrades to a speculative grade rating and if commercial paper access is affected. In particular, firms downgraded to speculative are about twice as likely to reduce debt as other firms. Rating upgrades do not affect subsequent capital structure activity, suggesting that firms target minimum rating levels.

Credit Rating Changes and Leverage Adjustments: Concurrent or Continual?

2014 ◽  
Vol 17 (04) ◽  
pp. 1450027 ◽  
Author(s):  
Min Maung ◽  
Reza H. Chowdhury
Keyword(s):  
Capital Structure ◽  
Credit Rating ◽  
Credit Ratings ◽  
Debt Ratio ◽  
Rating Changes ◽  
One Year ◽  
Rating Downgrades

Prior research has shown that credit downgrades affect firm's capital structure decision. However, after adjusting for biases associated with the use of market debt ratio and after controlling for simultaneity between credit ratings and leverage, we find that rating upgrades also play a role in firms' leverage. Contrary to previously reported findings, our evidence also indicates that the effect of rating downgrades on capital structure lasts for more than just one year.

scholarly journals EFFECT OF CREDIT RATING ON CAPITAL STRUCTURE: A STUDY ON NON-FINANCIAL FIRMS IN PAKISTAN

2012 ◽  
Vol 12 (1) ◽  
Author(s):  
Keyword(s):  
Capital Structure ◽  
Credit Rating ◽  
Stock Exchange ◽  
Credit Ratings ◽  
Least Square ◽  
Statistical Tool ◽  
Ordinary Least Square ◽  
Optimal Capital Structure ◽  
Financial Firms ◽  
The Impact

Purpose- Aim of this study was to investigate whether the credit rating is an important determinant other than the firm's characteristic to obtain optimal capital structure focusing on the research hypothesis that the firms with higher credit along with the other factors (FTOA, ROA and Size) tend to have more debt in their capital structure of firms rated by P?CR? and Karachi Stock Exchange (KSE). Methodology/Sample- For this research, sample size of 48 observations (3 years data of 16 firms) was taken on the basis of convenience sampling. Results obtained by using Ordinary Least Square Model (OLS) as statistical tool to test the hypothesis Findings- Analysis clearly suggested that credit ratings do have an impact on firm's capital structure. It was concluded that firms with higher credit ratings along with other factors (FTOA, ROA and Size) do not tend to have more debt in their capital structure. Implications- Outcomes of this research might help investors, debtors and other stakeholders of the firms (rated by PACRA) to understand the impact of credit rating on firm's debt ratio and the overall dynamics and mechanism of capital structure.

The impact of market sectors and rating agencies on credit ratings: global evidence

2019 ◽  
Vol 20 (5) ◽  
pp. 389-410
Author(s):  
Kerstin Lopatta ◽  
Magdalena Tchikov ◽  
Finn Marten Körner
Keyword(s):  
Credit Risk ◽  
Credit Rating ◽  
Credit Ratings ◽  
Content Type ◽  
Rating Agencies ◽  
Credit Rating Agency ◽  
Rating Agency ◽  
Investment Grade ◽  
The Impact ◽  
Rating Downgrades

Purpose 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. Design/methodology/approach 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. Findings 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. Originality/value 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.

Effects of credit rating changes on capital structure of Latin American firms

2019 ◽  
Vol 13 ◽  
pp. e154005
Author(s):  
Thiago Botta Paschoal ◽  
Matheus da Costa Gomes ◽  
Mauricio Ribeiro do Valle
Keyword(s):  
Capital Structure ◽  
Latin American ◽  
Method Of Moments ◽  
Credit Rating ◽  
Necessary Conditions ◽  
Panel Data Analysis ◽  
Generalized Method Of Moments ◽  
Speed Of Adjustment ◽  
Rating Changes ◽  
Rating Downgrades

This study investigates whether non-financial Latin American firms adjust their capital structure in order to maintain certain rating levels. The credit rating-capital structure (CR-CS) hypothesis suggests that firms assume less debt after rating downgrades, aiming to retrieve necessary conditions to restore a better rating. Through panel data analysis for the 2000-2014 period and by using the generalized method of moments (GMM), we show that a rating downgrade does not accelerate the speed of adjustment to the target, indicating that firms do not target minimum rating levels, as predicted by the CR-CS hypothesis. Although, rating changes are related to firms’ capital structure, we conclude that Latin American firms do not adjust their capital structure to maintain certain rating levels.

scholarly journals PENGARUH STRUKTUR UTANG, PERINGKAT KREDIT, DAN STRUKTUR MODAL TERHADAP IMBAL JASA AUDIT

2020 ◽  
Vol 28 (2) ◽  
pp. 84
Author(s):  
Adi Darmawan Ervanto ◽  
Andry Irwanto
Keyword(s):  
Capital Structure ◽  
Credit Rating ◽  
Negative Impact ◽  
Stock Exchange ◽  
Credit Ratings ◽  
Audit Fees ◽  
Risk Governance ◽  
Short Term ◽  
Natural Logarithm ◽  
Audit Fee

Introduction: The purpose of this study is to empirically examine any effect of short-term debt structure, credit ratings, and capital structure on the audit fee. The sample used in this study are the companies listed in the PT Pemeringkat Efek Indonesia (Pefindo) and the Indonesia Stock Exchange. Methods: Data were analyzed using linear regression.The independent variables in this study are the proportion of short-term debt, credit ratings, and capital structure. Dependent variable is audit fee. This research uses the control variables representing firm size, its complexity, and risk. Number of assets and current assets to total assets ratio represent the size of the company. Number of business segments and the proportion of export sales to total sales represent the complexity of the company. Risk represented by the ratio of short-term liabilities to total assets, short-term liabilities to total assets ratio, quick ratio, and return on assets. Results: Hypothesis testing shows that the proportion of short-term debt does not significantly influence audit fee. Ratings have a negative impact on the audit fees of listed companies in Indonesia's credit rating. Capital structure does not significantly influence audit fee. Conclusion and suggestion: This study has limitations that are audit fee is measured by the natural logarithm of the nominal value of professional fees expense presented in the financial statements of the company and there is a possibility of mediating variables such as risk governance and audit, in examining impact of the proportion of debt and capital structure on audit fee.

scholarly journals The impact of credit ratings on capital structure

2019 ◽  
Vol 11 (2) ◽  
pp. 226-245
Author(s):  
Bora Aktan ◽  
Şaban Çelik ◽  
Yomna Abdulla ◽  
Naser Alshakhoori
Keyword(s):  
Capital Structure ◽  
Credit Rating ◽  
Stock Exchange ◽  
Debt Crisis ◽  
Credit Ratings ◽  
Research Result ◽  
Small Sample ◽  
Linear Regression Models ◽  
Content Type ◽  
The Impact

Purpose The purpose of this paper is to empirically investigate the effect of real credit ratings change on capital structure decisions. Design/methodology/approach The study uses three models to examine the impact of credit rating on capital structure decisions within the framework of credit rating-capital structure hypotheses (broad rating, notch rating and investment or speculative grade). These hypotheses are tested by multiple linear regression models. Findings The results demonstrate that firms issue less net debt relative to equity post a change in the broad credit ratings level (e.g. a change from A- to BBB+). The findings also show that firms are less concerned by notch ratings change as long the firms remain the same broad credit rating level. Moreover, the paper indicates that firms issue less net debt relative to equity after an upgrade to investment grade. Research limitations/implications The study covers the periods of 2009 to 2016; therefore, the research result may be affected by the period specific events such as the European debt crisis. Moreover, studying listed non-financial firms only in the Tadawul Stock Exchange has resulted in small sample which may not be adequate enough to reach concrete generalization. Despite the close proximity between the GCC countries, there could be jurisdictional difference due to country specific regulations, policies or financial development. Therefore, it will be interesting to conduct a cross country study on the GCC to see if the conclusions can be generalized to the region. Originality/value The paper contributes to the literature by testing previous researches on new context (Kingdom of Saudi Arabia, KSA) which lack sophisticated comparable studies to the one conducted on other regions of the world. The results highlight the importance of credit ratings for the decision makers who are required to make essential decisions in areas such as financing, structuring or operating firms and regulating markets. To the best of the authors’ knowledge, this is the first study of its kind that has been applied on the GCC region.

Role of Credit Rating in determining Capital structure: Evidence from Non-Financial sector of Pakistan

2020 ◽  
Vol 38 (3) ◽  
Author(s):  
Shoaib Ali ◽  
Imran Yousaf ◽  
Muhammad Naveed
Keyword(s):  
Capital Structure ◽  
Credit Rating ◽  
Least Square ◽  
Annual Data ◽  
Leverage Ratio ◽  
Financial Decisions ◽  
Financial Firms ◽  
High Level ◽  
The Impact ◽  
The Capital Structure

This paper aims to examine the impact of external credit ratings on the financial decisions of the firms in Pakistan.  This study uses the annual data of 70 non-financial firms for the period 2012-2018. It uses ordinary least square (OLS) to estimate the impact of credit rating on capital structure. The results show that rated firm has a high level of leverage. Moreover, Profitability and tanagability are also found to be a significantly negative determinant of the capital structure, whereas, size of the firm has a significant positive relationship with the capital structure of the firm.  Besides, there exists a non-linear relationship between the credit rating and the capital structure. The rated firms have higher leverage as compared to the non-rated firms. The high and low rated firms have a low level of leverage, while mid rated firms have a higher leverage ratio. The finding of the study have practical implications for the manager; they can have easier access to the financial market by just having a credit rating no matter high or low. Policymakers must stress upon the rating agencies to keep improving themselves as their rating severs as the measure to judge the creditworthiness of the firm by both the investors and management as well.

Rating Agency Adjustments to GAAP Financial Statements and Their Effect on Ratings and Credit Spreads

2014 ◽  
Vol 90 (2) ◽  
pp. 641-674 ◽  
Author(s):  
Pepa Kraft
Keyword(s):  
Default Risk ◽  
Credit Rating ◽  
Credit Ratings ◽  
Balance Sheet ◽  
Financial Statements ◽  
Financial Statement ◽  
Credit Spread ◽  
Credit Spreads ◽  
Term Structures ◽  
Interest Expense

ABSTRACT I examine a dataset of both quantitative (hard) adjustments to firms' reported U.S. GAAP financial statement numbers and qualitative (soft) adjustments to firms' credit ratings that Moody's develops and uses in its credit rating process. I first document differences between firms' reported and Moody's adjusted numbers that are both large and frequent across firms. For example, primarily because of upward adjustments to interest expense and debt attributable to firms' off-balance sheet debt, on average, adjusted coverage (cash flow-to-debt) ratios are 27 percent (8 percent) lower and adjusted leverage ratios are 70 percent higher than the corresponding U.S. GAAP ratios. I then find that Moody's hard and soft rating adjustments are associated with significantly higher credit spreads and flatter credit spread term structures. Overall, the results indicate that Moody's quantitative adjustments to financial statement numbers and qualitative adjustments to credit ratings enable it to better capture default risk, consistent with it effectively processing both hard and soft information.

Uncertain Meanings of Risk

2018 ◽  
Author(s):  
Natalia Besedovsky
Keyword(s):  
Financial Markets ◽  
Credit Rating ◽  
Traditional Approach ◽  
Credit Ratings ◽  
Assessment Practices ◽  
Structured Finance ◽  
Rating Agencies ◽  
Measures Of Risk ◽  
Methodological Approaches ◽  
Ontological Uncertainty

This chapter studies calculative risk-assessment practices in credit rating agencies. It identifies two fundamentally different methodological approaches for producing ratings, which in turn shape the respective conceptions of credit risk. The traditional approach sees ‘risk’ as an only partially calculable and predictable set of hazards that should be avoided or minimized. This approach is particularly evident in the production of country credit ratings and gives rise to ordinal rankings of risk. By contrast, structured finance rating practices conceive of ‘risk’ as both fully calculable and controllable; they construct cardinal measures of risk by assuming that ontological uncertainty does not exist and that models can capture all possible events in a probabilistic manner. This assumption—that uncertainty can be turned into measurable risk—is a necessary precondition for structured finance securities and has become an influential imaginary in financial markets.

scholarly journals Numerical estimates of risk factors contingent on credit ratings

2021 ◽  
Author(s):  
T. Gärtner ◽  
S. Kaniovski ◽  
Y. Kaniovski
Keyword(s):  
Risk Factors ◽  
Financial Risk ◽  
Credit Rating ◽  
Likelihood Function ◽  
Adverse Outcome ◽  
Credit Ratings ◽  
Industry Sector ◽  
Random Events ◽  
Historical Transition ◽  
Industry Sectors

AbstractAssuming a favorable or an adverse outcome for every combination of a credit class and an industry sector, a binary string, termed as a macroeconomic scenario, is considered. Given historical transition counts and a model for dependence among credit-rating migrations, a probability is assigned to each of the scenarios by maximizing a likelihood function. Applications of this distribution in financial risk analysis are suggested. Two classifications are considered: 7 non-default credit classes with 6 industry sectors and 2 non-default credit classes with 12 industry sectors. We propose a heuristic algorithm for solving the corresponding maximization problems of combinatorial complexity. Probabilities and correlations characterizing riskiness of random events involving several industry sectors and credit classes are reported.

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