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Journal articles on the topic 'Credit ratings and credit risk'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Kiesel, Florian, and Jonathan Spohnholtz. "CDS spreads as an independent measure of credit risk." Journal of Risk Finance 18, no. 2 (2017): 122–44. http://dx.doi.org/10.1108/jrf-09-2016-0119.

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Purpose 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. Design/methodology/approach 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. Findings The empir

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2

Singagerda, Faurani Santi, Tulus Suryanto, and Jesscia Christina Sudjana. "Credit Risk-Return Puzzle: Asian Countries Representative." Journal of Accounting and Business Education 1, no. 1 (2017): 26. http://dx.doi.org/10.26675/jabe.v1i1.9747.

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<p>This research investigates the presence of Credit Risk-Return Puzzle on Indonesia, China, Japan and Singapore, by analyzing the relationship between credit risk and stock return with the utilization of credit ratings from Moody’s to represent credit risk. The data comprises of monthly data from January 2001 to December 2015, compiled in an unbalanced panel and then regressed with the Hausman-Taylor Estimator due to the presence of time-invariant variables such as countries and country classifications within the dataset.</p><p>The results from this research show that Credit

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3

Chodnicka-Jaworska, Patrycja. "Macroeconomic aspects of banks’ credit ratings." Equilibrium 12, no. 1 (2017): 101. http://dx.doi.org/10.24136/eq.v12i1.6.

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Research background: The practical analysis suggests that credit ratings are especially significant for banks. The literature review suggests that in previous analysis researchers usually took into consideration financial factors of the banks’ credit ratings methodology. This article analyses the impact of macroeconomic factors on the banks’ credit ratings. Purpose of the article: The paper examines and analyses the impact of the macroeconomic risk factors on the credit ratings received by banks. In the article, the methodology of credit risk assessment proposed by Moody’s Investor Servi

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Venkiteshwaran, Vinod. "Do asset sales affect firm credit risk? – Evidence from credit rating assignments." Managerial Finance 40, no. 9 (2014): 903–27. http://dx.doi.org/10.1108/mf-09-2012-0196.

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Purpose – Asset sales can have opposing effects on firm credit quality. On the one hand asset sales could signal increased credit risk resulting from distress or on the other hand they could improve internal liquidity and hence credit quality. Therefore the impact potential asset sales can have on credit quality is an empirical question and one that has previously not been examined in the literature. The paper aims to discuss these issues. Design/methodology/approach – Using credit ratings as a measure of firm credit quality, in ordered probit regressions, this study finds evidence consistent

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Jacobs Jr, Michael, Ahmet K. Karagozoglu, and Dina Naples Layish. "Credit risk signals in CDS market vs agency ratings." Journal of Risk Finance 17, no. 2 (2016): 194–217. http://dx.doi.org/10.1108/jrf-07-2015-0070.

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Purpose 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. Design/methodology/approach 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 participant

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Barth, Mary E., Gaizka Ormazabal, and Daniel J. Taylor. "Asset Securitizations and Credit Risk." Accounting Review 87, no. 2 (2011): 423–48. http://dx.doi.org/10.2308/accr-10194.

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ABSTRACT This study examines the sources of credit risk associated with asset securitizations and whether credit-rating agencies and the bond market differ in their assessment of this risk. Measuring credit risk using credit ratings, we find the securitizing firm's credit risk is positively related to the firm's retained interest in the securitized assets and unrelated to the portion of the securitized assets not retained by the firm. Measuring credit risk using bond spreads, we find the securitizing firm's credit risk is positively related to both the firm's retained interest in the assets an

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Ntsalaze, Zuziwe, Gideon Boako, and Paul Alagidede. "The impact of sovereign credit ratings on corporate credit ratings in South Africa." African Journal of Economic and Management Studies 8, no. 2 (2017): 126–46. http://dx.doi.org/10.1108/ajems-07-2016-0100.

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Purpose The purpose of this paper is to examine the impact of sovereign credit ratings on corporations in South Africa by assessing whether the sovereign rating assigned to South Africa by credit rating agencies acts as a ceiling/constraint for credit ratings assigned to corporations that operate within the country. The question of whether sovereign ratings are significant in determining corporate ratings was also explored. Design/methodology/approach To test the hypothesis regarding the rating of corporates relative to sovereigns, a longitudinal panel design was followed. The analysis employe

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8

Hilscher, Jens, and Mungo Wilson. "Credit Ratings and Credit Risk: Is One Measure Enough?" Management Science 63, no. 10 (2017): 3414–37. http://dx.doi.org/10.1287/mnsc.2016.2514.

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9

Lopatta, Kerstin, Magdalena Tchikov, and Finn Marten Körner. "The impact of market sectors and rating agencies on credit ratings: global evidence." Journal of Risk Finance 20, no. 5 (2019): 389–410. http://dx.doi.org/10.1108/jrf-09-2017-0145.

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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 examina

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Stellinga, Bart. "Why performativity limits credit rating reform." Finance and Society 5, no. 1 (2019): 20–41. http://dx.doi.org/10.2218/finsoc.v5i1.3016.

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The 2008 crisis made clear that credit rating agencies (CRAs) can contribute to systemic financial risk. Surprisingly, post-crisis reforms have hardly addressed the underlying problems, including rating agencies’ methodologies, their ratings’ homogeneity, and widespread market reliance on these signals. Current scholarship on CRA regulation blames policymakers’ unwillingness to fix systemic problems. This article draws on insights from the social studies of finance literature to provide a different explanation: the key obstacle is policymakers’ inability to fix these problems. The regulatory p

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Arora, Taruntej Singh. "Impact of Corporate Governance on Credit Ratings: An Empirical Study in the Indian Context." Indian Journal of Corporate Governance 13, no. 2 (2020): 140–64. http://dx.doi.org/10.1177/0974686220966808.

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Credit rating is the judgement of a credit rating firm of the creditworthiness of an entity as well as its ability to repay outstanding debt. Prior literature on credit ratings has majorly identified firm-specific characteristics as well as the characteristics of the debt issued as the primary factors affecting credit ratings. However, effective governance mechanisms can affect the credit ratings of a firm by way of their influence on a firm’s default risk. The present article is an attempt to discern the relationship between corporate governance and credit ratings by studying the Bombay Stock

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deHaan, Ed. "The Financial Crisis and Corporate Credit Ratings." Accounting Review 92, no. 4 (2017): 161–89. http://dx.doi.org/10.2308/accr-51659.

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ABSTRACT Credit ratings on many financial instruments failed to accurately portray default risk before the global financial crisis. I find no decline in the performance of corporate credit ratings during or after the crisis, indicating that the failures of ratings on financial instruments were due to conditions unique to the rating agencies' financial instruments divisions. Rather, the preponderance of tests indicate that corporate credit rating performance improves after the crisis, consistent with the rating agencies positively responding to public criticism and regulatory pressures. At the

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Karminsky, A. M., and N. F. Dyachkova. "Empirical study of the relationship between credit cycles and changes in credit ratings." Journal of the New Economic Association 48, no. 4 (2020): 138–60. http://dx.doi.org/10.31737/2221-2264-2020-48-4-6.

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The purpose of this study is to identify relationships between changes in ratings and the impact of credit cycles on them. The following methodology was used: we built up an applied statistical probit-model of multiple-choice to determine ratings changes. Our model includes a credit gap indicator for assessing the impact of the credit cycle. Our empirical research also includes a review of the time changes in the ratings during a ten-year period for developed and developing countries. The results of our study show that credit ratings are not only affected by cyclical changes within the credit

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Iyer, K. C., and Dhruba Purkayastha. "Credit Risk Assessment in Infrastructure Project Finance:Relevance of Credit Ratings." Journal of Structured Finance 22, no. 4 (2017): 17–25. http://dx.doi.org/10.3905/jsf.2017.22.4.017.

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Yusof, Norliza Muhamad, Iman Qamalia Alias, Ainee Jahirah Md Kassim, and Farah Liyana Natasha Mohd Zaidi. "Determining the Credit Score and Credit Rating of Firms using the Combination of KMV-Merton Model and Financial Ratios." Science and Technology Indonesia 6, no. 3 (2021): 105–12. http://dx.doi.org/10.26554/sti.2021.6.3.105-112.

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Credit risk management has become a must in this era due to the increase in the number of businesses defaulting. Building upon the legacy of Kealhofer, McQuown, and Vasicek (KMV), a mathematical model is introduced based on Merton model called KMV-Merton model to predict the credit risk of firms. The KMV-Merton model is commonly used in previous default studies but is said to be lacking in necessary detail. Hence, this study aims to combine the KMV-Merton model with the financial ratios to determine the firms’ credit scores and ratings. Based on the sample data of four firms, the KMV-Merton mo

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Ruddy, John A. "An Analysis of Bank Financial Strength Ratings and Credit Rating Data." Risks 9, no. 9 (2021): 155. http://dx.doi.org/10.3390/risks9090155.

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In this study, data from two credit rating agencies are analyzed to consider how different Bank Financial Strength Ratings and Credit Ratings from two rating agencies compare. To my knowledge, prior research has not analyzed Bank Financial Strength Ratings from different rating agencies, nor has it compared Bank Financial Strength Ratings to general credit ratings. These facts make this research unique. Univariate analyses are utilized to show relationships in the ratings data, along with parametric and non-parametric tests to make statistical inferences about the ratings data. There are five

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Meyer, Daniel, and Lerato Mothibi. "The impact of risk rating agencies decisions on investment and economic growth in South Africa." 11th GLOBAL CONFERENCE ON BUSINESS AND SOCIAL SCIENCES 11, no. 1 (2020): 109. http://dx.doi.org/10.35609/gcbssproceeding.2020.11(109).

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Over the last decade, the South African economy has endured prevailing economic challenges including weak economic growth, unreliable electricity supply, rising fiscal deficits, sub-duded investment inflows and the inexorable rise in government debt alongside the expected impact of the corona virus pandemic. Credit ratings have greatly evolved making them key elements in the modern financial markets because of their opinions of credit worthiness, as many investors across the globe relay heavily on their opinions. South Africa unlike many of its developing counterparts, has since struggled to m

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Pasricha, Puneet, Dharmaraja Selvamuthu, and Viswanathan Arunachalam. "Markov regenerative credit rating model." Journal of Risk Finance 18, no. 3 (2017): 311–25. http://dx.doi.org/10.1108/jrf-09-2016-0123.

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Purpose Credit ratings serve as an important input in several applications in risk management of the financial firms. The level of credit rating changes from time to time because of random credit risk and, thus, can be modeled by an appropriate stochastic process. Markov chain models have been widely used in the literature to generate credit migration matrices; however, emergent empirical evidences suggest that the Markov property is not appropriate for credit rating dynamics. The purpose of this article is to address the non-Markov behavior of the rating dynamics. Design/methodology/approach

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Mali, Dafydd, and Hyoungjoo Lim. "Does corporate ownership affect credit risk?: An investment grade vs non-investment grade firm analysis – evidence from South Korea." Corporate Ownership and Control 13, no. 4 (2016): 38–49. http://dx.doi.org/10.22495/cocv13i4p4.

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A credit rating indicates a firm’s risk of financial default. Using 1) controlling shareholders’ ownership and 2) foreign investors’ ownership as proxies for corporate governance, we investigate whether corporate ownership structure influences a credit rating agencies’ perception of risk. Using a sample of 1,213 KRX firm-year observations, and a t+1 approach, we find that firms with higher foreign ownership have higher credit ratings compared to those with lower foreign ownership. Moreover, we find that higher percentage of shareholder ownership does not affect credit ratings for our initial s

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Adelson, Mark, and David Jacob. "Strengthening credit rating integrity." Journal of Financial Regulation and Compliance 23, no. 4 (2015): 338–53. http://dx.doi.org/10.1108/jfrc-11-2014-0047.

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Purpose – 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. Design/methodology

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21

Lee, Yen-Jung. "The Effects of Employee Stock Options on Credit Ratings." Accounting Review 83, no. 5 (2008): 1273–314. http://dx.doi.org/10.2308/accr.2008.83.5.1273.

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ABSTRACT: This paper examines whether outstanding employee stock options (ESOs), which represent the firm’s contractual obligation to deliver shares upon ESO exercise, affect firms’ credit ratings. I hypothesize that outstanding ESOs play two information roles—(1) suggesting equity infusion, and (2) predicting share repurchases—that help credit-rating agencies evaluate the issuing company’s debt service ability. Consistent with these hypothesized roles, results indicate that the present values of expected cash proceeds and tax benefits from ESO exercise have favorable effects on credit ratings

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van de Ven, Rick, Shaunak Dabadghao, and Arun Chockalingam. "Assigning Eurozone sovereign credit ratings using CDS spreads." Journal of Risk Finance 19, no. 5 (2018): 478–512. http://dx.doi.org/10.1108/jrf-06-2017-0096.

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Purpose The credit ratings issued by the Big 3 ratings agencies are inaccurate and slow to respond to market changes. This paper aims to develop a rigorous, transparent and robust credit assessment and rating scheme for sovereigns. Design/methodology/approach This paper develops a regression-based model using credit default swap (CDS) data, and data on financial and macroeconomic variables to estimate sovereign CDS spreads. Using these spreads, the default probabilities of sovereigns can be estimated. The new ratings scheme is then used in conjunction with these default probabilities to assign

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Leggio, Karyl B., Yoon S. Shin, and Yuxing Yan. "Assessment of Credit Ratings and Credit Risk Models on Public Bonds." Journal of Fixed Income 30, no. 4 (2021): 65–80. http://dx.doi.org/10.3905/jfi.2021.1.104.

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CAPECI, JOHN. "CREDIT RISK, CREDIT RATINGS, AND MUNICIPAL BOND YIELDS: A PANEL STUDY." National Tax Journal 44, no. 4.1 (1991): 41–56. http://dx.doi.org/10.1086/ntj41788921.

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Zhang, Yajing, and Guotai Chi. "A credit rating model based on a customer number bell-shaped distribution." Management Decision 56, no. 5 (2018): 987–1007. http://dx.doi.org/10.1108/md-03-2017-0232.

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Purpose The purpose of this paper is to split loan customers to different credit ratings to ensure the results that show that customers with lower credit ratings have higher loss rates, and the number of customers that satisfies the bell-shaped distribution. Hence, the number of credit ratings, the distribution of the rated obligors among ratings can achieve a meaningful differentiation of risk, which can avoid the loan pricing confusion. Design/methodology/approach The authors introduce a multi-objective programming to establish the credit rating model. Objective function 1 minimizes the abso

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Khromova, Ella. "Dynamic Mapping of Probability of Default and Credit Ratings of Russian Banks." Journal of Corporate Finance Research / Корпоративные Финансы | ISSN: 2073-0438 14, no. 4 (2020): 31–46. http://dx.doi.org/10.17323/j.jcfr.2073-0438.14.4.2020.31-46.

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Investors are interested in a quantitative measure of banks’ credit risk. This paper maps the credit ratings of Russian banks to default probabilities for different time horizons by constructing an empirical dynamic calibration scale. As such, we construct a dynamic scale of credit risk calibration to the probability of default (PD).Our study is based on a random sample of 395 Russian banks (86 of which defaulted) for the period of 2007-2017. The scale proposed by this paper has three features which distinguish it from existing scales: dynamic nature (quarterly probability of default estimates

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Jang, Ga-Young, Hyoung-Goo Kang, Ju-Yeong Lee, and Kyounghun Bae. "ESG Scores and the Credit Market." Sustainability 12, no. 8 (2020): 3456. http://dx.doi.org/10.3390/su12083456.

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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

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Demoussis, Michael, Konstantinos Drakos, and Nicholas Giannakopoulos. "The impact of sovereign ratings on euro zone SMEs’ credit rationing." Journal of Economic Studies 44, no. 5 (2017): 745–64. http://dx.doi.org/10.1108/jes-03-2016-0046.

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Purpose The purpose of this paper is to investigate credit rationing across firms in euro zone countries, as it relates to its own sovereign credit ratings. Design/methodology/approach The authors utilize firm-level data from the Survey on Access to Finance of Enterprises for the period 2009-2013 conducted by the European Central Bank. Findings A negative association between the rating of sovereign creditworthiness and credit rationing is identified, while credit rationing varies substantially even among countries with the highest quality of sovereign bonds. Credit rationing is lower in sovere

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Sethuraman, Mani. "The Effect of Reputation Shocks to Rating Agencies on Corporate Disclosures." Accounting Review 94, no. 1 (2018): 299–326. http://dx.doi.org/10.2308/accr-52114.

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ABSTRACT This paper explores the effect of a credit rating agency's (CRA) reputation on the voluntary disclosures of corporate bond issuers. Academics, practitioners, and regulators disagree on the informational role played by major CRAs and the usefulness of credit ratings in influencing investors' perception of the credit risk of bond issuers. Using management earnings forecasts as a measure of voluntary disclosure, I find that investors demand more (less) disclosure from corporate bond issuers when the ratings become less (more) credible. In addition, using content analytics, I find that bo

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Meyer, Helen. "Identity thieves place credit ratings at risk." Computers & Security 16, no. 3 (1997): 213. http://dx.doi.org/10.1016/s0167-4048(97)84539-7.

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Kuang, Yu Flora, and Bo Qin. "Credit Ratings and CEO Risk‐Taking Incentives." Contemporary Accounting Research 30, no. 4 (2013): 1524–59. http://dx.doi.org/10.1111/1911-3846.12005.

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Cantor, Richard, and Frank Packer. "Sovereign risk assessment and agency credit ratings." European Financial Management 2, no. 2 (1996): 247–56. http://dx.doi.org/10.1111/j.1468-036x.1996.tb00040.x.

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Gill, Suveera. "An Analysis of Defaults of Long-term Rated Debts." Vikalpa: The Journal for Decision Makers 30, no. 1 (2005): 35–50. http://dx.doi.org/10.1177/0256090920050104.

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Lately, the credit rating agencies have been the subject of significant criticism for failing to warn the investors of the defaults well in advance. Investors in long-term debt instruments are usually risk averse, buy-and-hold types; and hence, for them, the variability of investment-grade default rates is particularly important since they employ simple investment-grade rating cut-offs in the design of their investment eligibility plan. According to ICRA (Investment Information and Credit Rating Agency of India) and the other credit rating agencies, default means that the company has either al

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Gmehling, Philipp, and Pierfrancesco La Mura. "A Bayesian inference model for the credit rating scale." Journal of Risk Finance 17, no. 4 (2016): 390–404. http://dx.doi.org/10.1108/jrf-04-2016-0055.

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Purpose This paper aims to provide a theoretical explanation of why credit rating agencies typically disclose credit risk of issuers in classes rather than publishing the qualitative ranking those classes are based upon. Thus, its goal is to develop a better understanding of what determines the number and size of rating classes. Design/methodology/approach Investors expect ratings to be sufficiently accurate in estimating credit risk. In a theoretical model framework, it is therefore assumed that credit rating agencies, which observe credit risk with limited accuracy, are careful in not miscla

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RUBINSTEIN, PETER, LEO M. TILMAN, and ALAN TODD. "Thoughts on Credit Risk Diversification: Comparing Credit Ratings Volatility Across Asset Classes." Journal of Risk Finance 3, no. 3 (2002): 24–35. http://dx.doi.org/10.1108/eb043492.

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Prorokowski, Lukasz. "Revised standardised approach for credit risk in practice." Journal of Financial Regulation and Compliance 26, no. 1 (2018): 87–102. http://dx.doi.org/10.1108/jfrc-10-2016-0093.

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Purpose Focusing on delivering practical implications, the purpose of this paper is to show optimal ways of calculating risk weights for public sector entities (PSEs) under the standardised approach in credit risk. Focusing on the changing regulatory background, this paper aims to explain the proposed revisions to the standardised approach for credit risk. Where necessary, upon the review of the forthcoming standards, this paper attempts to indicate room for improvement for policymakers and flag areas of potential ambiguity for practitioners. Design/methodology/approach This paper discusses an

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AlHares, Aws, Collins Ntim, David King, and Ron Byrne. "Does ownership structure improve credit ratings?" Journal of Governance and Regulation 7, no. 2 (2018): 22–33. http://dx.doi.org/10.22495/jgr_v7_i2_p3.

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This study seeks to examine the impact of Block Ownership structure on Credit Ratings in OECD countries. This research seeks to contribute to the extant literature by exploring the effects of Corporate Governance (CG) mechanisms on corporate credit ratings. The study uses a panel data of 200 companies from Anglo American and European countries between 2010 and 2014. The ordinary least square regression is used to examine the relationships. Additionally, to alleviate the concern of potential endogeneity, we use fixed effect regression, two-stage least squares using instrumental variables. The r

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Hanus, I., I. Plikus, and T. Zhukova. "DEBTOR RATING AS A TOOL OF DEBT MANAGEMENT." Vìsnik Sumsʹkogo deržavnogo unìversitetu, no. 3 (2020): 121–29. http://dx.doi.org/10.21272/1817-9215.2020.3-13.

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IFRS 9 “Financial Instruments” introduced a new model of impairment based on expected credit losses, in which the impairment is based on expected credit losses, and the provision for losses is recognized before the credit loss, i.e. companies recognize losses immediately after initial recognition of the financial asset and revise the amount of the provision for expected credit losses at the reporting date. To create a provision for credit losses, IFRS 9 allows using several practical tools, including the rating debtors’ method. However, IFRS 9 does not express a clear opinion on how the expect

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Hašková, Simona. "The fuzzy approach for estimating the creditworthiness and credit risk of issuers of corporate bonds." SHS Web of Conferences 61 (2019): 01003. http://dx.doi.org/10.1051/shsconf/20196101003.

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The uncertainty in the financial market is often perceived as a risk of deviation from expected results. However, uncertainty is associated with vagueness in the sense of ambiguity or obscurity, which, unlike the risk, is not describable in the form of deterministic or stochastic models. Given the vagueness of the data entering the credit risk assessment models, the fuzzy decision-making process is introduced in the theoretical part and implemented in the application part as an effective alternative to standard models. The fuzzy approach is used to address the problem of the creditworthiness o

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Gul, Ferdinand A., and John Goodwin. "Short-Term Debt Maturity Structures, Credit Ratings, and the Pricing of Audit Services." Accounting Review 85, no. 3 (2010): 877–909. http://dx.doi.org/10.2308/accr.2010.85.3.877.

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ABSTRACT: Short-term debt and credit ratings have benefits for financial reporting quality that may be associated with lower audit fees. Using U.S. data for 2003 through 2006, we find that short-term debt is negatively related to audit fees for firms rated by Standard & Poor’s, consistent with more monitoring and better governance mechanisms in firms with higher short-term debt. Credit ratings quality is negatively related to audit fees, consistent with ratings quality reflecting a firm’s liquidity risk, governance mechanisms, and monitoring from rating agencies. We also find that the nega

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Bonsall, Samuel, Kevin Koharki, and Monica Neamtiu. "The Effectiveness of Credit Rating Agency Monitoring: Evidence from Asset Securitizations." Accounting Review 90, no. 5 (2015): 1779–810. http://dx.doi.org/10.2308/accr-51028.

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ABSTRACT This study investigates how differences between the rating agencies' initial (at the date of debt issuance) and subsequent (post-issuance) monitoring incentives affect securitizing banks' rating accuracy. We hypothesize that the agencies have stronger incentives to monitor issuers when providing initial versus post-issuance ratings. We document that initial ratings are positively associated with off-balance sheet securitized assets and incrementally associated with on-balance sheet retained securities. However, subsequent ratings fail to capture current exposure to off-balance sheet s

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Kariya, Takeaki, Yoshiro Yamamura, and Koji Inui. "Empirical Credit Risk Ratings of Individual Corporate Bonds and Derivation of Term Structures of Default Probabilities." Journal of Risk and Financial Management 12, no. 3 (2019): 124. http://dx.doi.org/10.3390/jrfm12030124.

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Undoubtedly, it is important to have an empirically effective credit risk rating method for decision-making in the financial industry, business, and even government. In our approach, for each corporate bond (CB) and its issuer, we first propose a credit risk rating (Crisk-rating) system with rating intervals for the standardized credit risk price spread (S-CRiPS) measure presented by Kariya et al. (2015), where credit information is based on the CRiPS measure, which is the difference between the CB price and its government bond (GB)-equivalent CB price. Second, for each Crisk-homogeneous class

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Fieberg, Christian, Richard Lennart Mertens, and Thorsten Poddig. "The relevance of credit ratings over the business cycle." Journal of Risk Finance 17, no. 2 (2016): 152–68. http://dx.doi.org/10.1108/jrf-08-2015-0079.

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Purpose Credit market models and the microstructure theory of the ratings market suggest that information provided by credit rating agencies becomes more relevant in recessions when agency costs are high and less relevant in expansions when agency costs are low. The purpose of this paper is to empirically test these hypotheses with regard to equity markets. Design/methodology/approach The authors use business cycle identification algorithms to map rating events (credit rating changes and watchlist inclusions) to business cycle phases and apply the event study methodology. The results are backe

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Trujillo-Ponce, Antonio, Reyes Samaniego-Medina, and Clara Cardone-Riportella. "EXAMINING WHAT BEST EXPLAINS CORPORATE CREDIT RISK: ACCOUNTING-BASED VERSUS MARKET-BASED MODELS." Journal of Business Economics and Management 15, no. 2 (2013): 253–176. http://dx.doi.org/10.3846/16111699.2012.720598.

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This paper uses a sample of 2,186 credit default swap spreads quoted in the European market during the period 2002–2009 to empirically analyze which model – accounting- or market-based – better explains corporate credit risk. We find little difference in the explanatory power of these two approaches. Our results indicate that a comprehensive model that combines accounting- and market-based variables is the best option to explain the credit risk, suggesting that both types of data are complementary. We also demonstrate that the explanatory power of credit risk models is particularly strong duri

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Bao, May Xiaoyan, and Yixin Liu. "Level 3 Assets and Credit Risk." Review of Pacific Basin Financial Markets and Policies 21, no. 01 (2018): 1850003. http://dx.doi.org/10.1142/s0219091518500030.

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We examine the impact of Level 3 assets held by nonfinancial companies on credit risk. Specifically, we investigate how the pricing uncertainty of Level 3 assets is reflected in credit ratings, corporate bond yield spreads, and incidences of bond covenants. We find that higher holdings of Level 3 assets are associated with lower credit ratings, higher yield spreads, especially for Level 3 assets sample, and incidences of bondholder-friendly covenants in the bond issues. Our findings are robust to the treatment of sample selection bias and the influence of macroeconomic factors. In addition, ou

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Penikas, Henry. "The review of the open challenges in the IRB loan portfolio credit risk modeling." Model Assisted Statistics and Applications 15, no. 4 (2020): 371–88. http://dx.doi.org/10.3233/mas-200508.

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The Basel Committee on Banking Supervision finalized the Basel III accord in the December 2017 and launched the set of its standards – the Basel Framework – in December 2019. Both documents allow bank to use mathematical models for the credit risk estimation. There are quantitative and qualitative requirements for models to be allowed for use in the prudential regulation of banks. The approach is called an Internal-Ratings-Based one (IRB). This paper aims at discussing a set of issues related to IRB credit risk modeling and such model estimates use. Those issues include data pooling in the cre

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Ferri, Giovanni, and Li-Gang Liu. "How Do Global Credit-Rating Agencies Rate Firms from Developing Countries?" Asian Economic Papers 2, no. 3 (2003): 30–56. http://dx.doi.org/10.1162/asep.2003.2.3.30.

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This paper examines the information content of firm ratings. We disentangle the relative contribution to firms' ratings of sovereign risks and of the individual firms' performance indicators employed by rating agencies. We reach three conclusions. First, the contribution of sovereign risk to firm ratings is high in developing countries but is negligible in developed countries. Second, even after controlling for the “country ceiling effect” (i.e., the constraint put on the private firms' rating by the rating of the country in which the firms operate), the information content of ratings for firm

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Wu, Hsu-Che, Ya-Han Hu, and Yen-Hao Huang. "Two-stage credit rating prediction using machine learning techniques." Kybernetes 43, no. 7 (2014): 1098–113. http://dx.doi.org/10.1108/k-10-2013-0218.

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Purpose – Credit ratings have become one of the primary references for financial institutions to assess credit risk. Conventional credit rating approaches mainly concentrated on two-class classification (i.e. good or bad credit), which lacks adequate precision to perform credit risk evaluations in practice. In addition, most of previous researches directly focussed on employing various data mining techniques, but rare studies discussed the influence of data preprocessing before classifier construction. The paper aims to discuss these issues. Design/methodology/approach – This study considers n

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BIELECKI, TOMASZ R., IGOR CIALENCO, and ISMAIL IYIGUNLER. "COLLATERALIZED CVA VALUATION WITH RATING TRIGGERS AND CREDIT MIGRATIONS." International Journal of Theoretical and Applied Finance 16, no. 02 (2013): 1350009. http://dx.doi.org/10.1142/s021902491350009x.

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In this paper we discuss the issue of computation of the bilateral credit valuation adjustment (CVA) under rating triggers, and in presence of ratings-linked margin agreements. Specifically, we consider collateralized OTC contracts, that are subject to rating triggers, between two parties — an investor and a counterparty. Moreover, we model the margin process as a functional of the credit ratings of the counterparty and the investor. We employ a Markovian approach for modeling of the rating transitions of the two parties to the contract. In this framework, we derive the representation for bila

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Fauser, Daniel V., and Andreas Gruener. "Corporate Social Irresponsibility and Credit Risk Prediction: A Machine Learning Approach." Credit and Capital Markets – Kredit und Kapital: Volume 53, Issue 4 53, no. 4 (2020): 513–54. http://dx.doi.org/10.3790/ccm.53.4.513.

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This paper examines the prediction accuracy of various machine learning (ML) algorithms for firm credit risk. It marks the first attempt to leverage data on corporate social irresponsibility (CSI) to better predict credit risk in an ML context. Even though the literature on default and credit risk is vast, the potential explanatory power of CSI for firm credit risk prediction remains unexplored. Previous research has shown that CSI may jeopardize firm survival and thus potentially comes into play in predicting credit risk. We find that prediction accuracy varies considerably between algorithms

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