Credit Rating Downgrades Research Articles

Does the impact of credit rating downgrade on bond returns vary by region: Empirical evidence from China

Utilizing trading data from corporate and enterprise bonds that experienced credit rating downgrades between 2012 and 2022, this study employs event study methodology and regression analysis to examine the regional differences in the impact of credit rating downgrades on bond pricing and the mechanisms behind these effects. The study found that, during the window period when the bond credit rating is downgraded, there is a significant difference in the cumulative abnormal return of bonds between the eastern and non-eastern regions. Heterogeneity analysis indicates that bonds with higher credit ratings and those issued by non-state-owned enterprises are more significantly affected by credit rating downgrades. This study provides empirical evidence of regional disparities in the impact of credit rating downgrades, and proposes a theoretical mechanism whereby differences in the degree of marketization influence these effects through varying expectations of government implicit guarantees. The findings offer a theoretical foundation for optimizing decision-making by participants in the Chinese bond market.

Impact of credit rating downgrades and tightness of accounting standards on earnings management in listed SMES

Due to its nature, funding remains the main problem for listed small and medium-sized enterprises (SMEs) globally. To overcome such a problem, there is a trend of using credit rating as the benchmark to appraise funding opportunities and applications in listed SMEs. As credit rating levels vary across time, subject to the performance of the listed SMEs, changes in the credit rating levels might trigger attention from listed SMEs, and actions might then be taken by the management to ensure that the credit rating is at the desired level. Since the literature in this strand of study is limited, this study aimed to examine the effect of credit rating downgrade and tightness of accounting standards on earnings management in listed SMEs. Employing a 2x3 between-subjects experiment manipulating credit rating downgrades (category or notch) and tightness of accounting standards (less tight, moderately tight, tight), it is evidenced that credit rating downgrades, especially notch downgrades, lead to more earnings management behaviors in the presence of a tight and less tight set of accounting standards. Different classifications of credit rating downgrades – notches and categories – will have different implications for earnings management based on the extent to which they are subject to external monitoring. As a practical matter, it is recommended that regulators exercise equal monitoring regardless of whether credit rating downgrades occur by category or notch.

Credit rating downgrades and systemic risk

We examine whether changes in issuer credit ratings by the three main providers are associated with changes in systemic risk. First, we find that rating downgrades result in an increase in bank systemic risk, whereas upgrades do not proportionally reduce systemic risk. Second, we document that the positive relationship between rating downgrades and systemic risk can be mitigated by accounting-based stability factors, such as profitability and capital, but also enhanced by sovereign rating downgrades. Finally, we show that sovereign rating downgrades have a greater effect on bound banks’ systemic risk compared to non-bound banks.

Do firms manage earnings after a downgrade in their credit rating?

PurposeThis paper aims to examine whether firms engage in earnings management immediately after experiencing a downgrade in their credit rating.Design/methodology/approachThis paper uses fixed-effects regression models to examine real- and accrual-based earnings management after firms experience a downgrade in their credit rating.FindingsInconsistent with prior studies where firms are reported to opportunistically increase their earnings prior to a credit rating event, this paper finds that firms use income-decreasing earnings management after their ratings are downgraded. This paper also finds that firms downgraded to below the investment grade rating not only significantly reduce both abnormal cash flows and discretionary accruals but also report larger asset impairments, suggesting that these firms exploit the rating downgrade to employ a big bath accounting.Practical implicationsThe results of this paper have practical implications for investors fixating on firm earnings after a credit rating downgrade, for shareholders of downgraded firms and regulators such as credit rating agencies.Originality/valueThe findings of this study contribute to the thin literature on earnings management after changes in credit rating by shedding lights on earnings management after a rating downgrade and complement the literature on the accounting choice of financially distressed firms. The empirical evidence documented in this study suggests that the occurrence of income-decreasing earnings management is not limited to only after a sovereign country rating downgrade as documented in a prior study but also occurs after a rating downgrade not associated with this event.

Default Risk and Option Returns

This paper studies the effects of default risk on expected equity option returns. In the cross-section, expected delta-hedged equity option returns have a negative relation with default risk measured by credit ratings or default probability. In the time series, credit rating downgrades (upgrades) lead to a decrease (increase) in the firm’s delta-hedged option return. Our results are consistent with a stylized capital structure model in which the negative relation between option returns and default risk is driven by firm leverage and asset volatility. This paper was accepted by Lukas Schmid, finance. Funding: A. Vasquez thanks the Asociación Mexicana de Cultura A.C. for financial support. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4796 .

Intrafirm Knowledge Sharing in the Investment Research Industry

We study interdepartment knowledge sharing in an investment research setting where the benefits are potentially significant for the brokerage and the capital market, but so are the frictions impeding it. Using hand-collected data on equity analyst access to in-house debt research expertise, we find significant benefits to equity analysts in the form of improved ability to forecast cash flows and to anticipate credit rating downgrades. Moreover, we find evidence that access to management and research expertise underlie in-house debt analysts’ capacity to generate information beneficial to equity analysts. Finally, these benefits exist only in the presence of a collaborative brokerage culture or debt-equity analyst collocation, consistent with these factors promoting knowledge sharing in the investment research industry. This paper was accepted by Brian Bushee, accounting. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4809 .

Credit rating downgrades and stock price crash risk: International evidence

We document a significant decline in the likelihood of firm-specific stock price crashes after the announcement of credit rating downgrades in 69 countries. This finding supports the argument that credit rating agencies (CRAs) contribute to the disseminating of negative information in the equity market by issuing rating downgrades. Our results remain robust after various tests for endogeneity. Further analysis shows that the negative relationship between rating downgrades and stock price crashes is amplified by information opacity. These findings shed light on the role of CRAs in promoting the flow of negative information into the equity market and enhancing its stability.

신용등급과 기업의 혁신활동

This study examines the impact of credit ratings on corporate innovation activities. A sample of domestic securities-listed companies is selected, and changes in innovation activities are investigated when firms exhibit high sensitivity to credit ratings. Credit rating data from December settlement companies, spanning the period from 2002 to 2019, excluding the financial industry, is employed. A total of 2,179 company-year observations are used, which include corporate patent data as a proxy for measuring innovation performance, to examine the relationship between credit ratings and innovation activities. Furthermore, the study analyzes how these relationships vary across high-tech and non-high-tech industries, as well as investment ratings and speculative ratings.
 The empirical analysis reveals a significant positive relationship between the sensitivity of firms to credit ratings and their innovation activities. Specifically, firms that are more sensitive to credit rating downgrades show an increase in innovation activities, while no significant results are found for credit rating upgrades. This suggests that firms with a higher likelihood of credit rating downgrades are more likely to actively pursue innovation activities to maintain their current credit rating. Moreover, this asymmetric relationship between credit ratings and innovation is more pronounced in high-tech industries compared to non-high-tech industries, and in investment-rated firms compared to speculative-rated firms. Based on these empirical findings, this study provides important implications for stakeholders and financial market participants regarding the relationship between credit ratings and innovation.

The Impact of CEO IT Ability on Bank Loan Terms

ABSTRACT Although the role that information technology (IT) executives’ expertise has in firm outcomes is well documented, little empirical work investigates the effect of the IT ability of non-IT executives on firm outcomes. We apply upper echelons theory and create a unique measure of chief executive officer (CEO) IT ability to empirically investigate its impact on bank loan pricing and nonpricing terms. Examining a sample of firms between 2002 and 2017, we find that CEO IT ability is associated with lower cost of debt, less collateral, fewer loan covenants, and fewer credit rating downgrades. Further, we show that our results are not due to high tech firms and are incremental to firm-level IT capability. Our results extend upper echelons theory and suggest that IT ability is an important CEO characteristic that can be influential in improving lending outcomes.

The Impact of Credit Rating Announcements on the Efficiency of the Stock Market

Taking the data of China's listed banks from 2015 to 2021 as a sample, this paper uses the event study method to analyze the impact of credit rating announcements on the effectiveness of the stock market. The results indicate that credit rating announcements have no significant impact on stock returns, and the market is in a semi strong form efficient state. By observing the excess returns of stocks after credit rating downgrades and upgrades, it is found that the excess returns after rating downgrades are not significantly negative, and the market is in a semi strong form efficient state; The rating upgrade has a significant positive impact on stock returns, indicating that the market is in a weakly efficient state.

Credit ratings and firm innovation: Evidence from sovereign downgrades

This study investigates the relationship between credit ratings and firm innovation activities using a cross-country sample over the 1995–2020 period. Exploiting the setting of rating agencies’ sovereign ceiling policies, our main analysis shows that a one-notch reduction in corporate credit ratings engendered by sovereign downgrades, on average, leads to a 5.90% reduction in research and development (R&D) spending. We identify the substitution of external acquisitions for internal expenditures and the increase in creditor control as the underlying mechanisms of the causal relation. Moreover, the negative impact of credit rating downgrades on R&D investment results in deterioration in patent output and firm performance. The cross-sectional analysis shows that the observed effects on innovation and firm performance are concentrated in firms with higher external finance dependence or more growth options.

Insiders' stock pledging disclosures and credit ratings: Evidence from India

We examine the impact of insiders' stock pledging disclosures on credit ratings of different debt instruments in India. The rating agencies extend a negative response in the form of low credit ratings for pledging firms compared to non-pledging firms - irrespective of any particular debt choice (private versus public) and debt maturity (short-term versus long-term). Insider stock pledging increases the likelihood of credit rating downgrade and the rating-watch status. It contains information about pledging firms' debt-servicing capacity and adversely affects credit ratings for firms with higher information asymmetry. Our findings also support an increase in the cost of debt for pledging firms.

Credit ratings and corporate risk-taking behavior: evidence from Korea

ABSTRACT We study the period following the 1997 Asian financial crisis to show that the credit rating downgrades affect corporate risk-taking behaviour. We treat the crisis as an exogenous shock that led to improvements in the informativeness of Korea’s credit rating system, and we determine that firms that have experienced credit rating downgrades reduce their risk-taking following the crisis. However, we show that this impact is less pronounced for chaebol-affiliated firms. Furthermore, we present chaebol firms’ characteristics that mitigate the negative impact of credit rating downgrades on their risk-taking behaviour – high net internal capital flow and large ownership concentration. (JEL G24, G32)

Qualitative Disclosure and Credit Analysts’ Soft Rating Adjustments

Using both dictionary-based and topic modelling approaches, we examine whether and how credit analysts use borrowers’ qualitative disclosures to extract information pertaining to credit risk in making their assessments. We first decompose publicly-available ratings into qualitative factors (soft adjustments) and quantitative factors (hard adjustments). We find that credit analysts’ soft adjustments, but not the hard adjustments, reflect information in borrowers’ qualitative disclosures. Next, our results indicate that the association between firms’ qualitative disclosures and soft adjustments varies depending upon the rating agency’s reliance on public disclosure, access to management, and overall market uncertainty. Finally, we examine whether analysts’ use of credit risk-relevant information from borrowers’ qualitative disclosures increases the informativeness of credit rating downgrades. We find that the credit rating downgrades of borrowers that provide more qualitative disclosures are more informative than those who do not; however, the increase in informativeness diminishes after the Dodd-Frank Act, when legal liability and regulatory penalties for credit rating agencies increased.

The effect of credit rating downgrades along the supply chain

PurposeThis study aims to examine the information transfer effects of customers’ credit rating downgrades on supplier firms.Design/methodology/approachIn this study, the authors use suppliers’ cumulative abnormal returns around customers’ credit rating downgrade events to identify how shocks to customer credit impact supplier equity prices. The authors also incorporate ordinary least squares and weighted least squares regressions regression analysis of the determinants of supplier market response to customer downgrades.FindingsThe authors find that customer credit rating downgrades present significant negative shocks to the stock prices of supplier firms. Moreover, the authors show that the information transfer effects are determined by both firm- and industry-level factors, including the market anticipation of downgrades, the strength of the customer–supplier linkage, the industry rivals’ reactions to the downgrades and investor attention. The authors also find that the likelihood that a supplier will receive a rating downgrade is significantly higher following its primary customer firm’s downgrade.Originality/valueTo the best of the authors’ knowledge, this paper is the first to explore the information transfer effects of credit rating downgrades on primary stakeholders within the supply chain. The authors document that customer–supplier networks have valuable implications for the spillover effect across debt and equity holders. Information about customers’ financial stress is incorporated into suppliers’ equity prices outside of the context of customer bankruptcy.

Testing Russian Stock Market Efficiency Using Event Studies: Impact of Credit Ratings Changes

Event study is a widespread technique for testing the semi-strong form of the market efficiency hypothesis. Among traditionally studied events, changes in corporate credit ratings by rating agencies have a special importance, since rating agencies use both publicly available and insider information. Studies of developed and emerging markets point to different reactions of stock prices to rating upgrades and downgrades and identify several factors affecting the scale of this effect, including the size and liquidity of the stock market, the level of regulation of the industry, the market capitalization of the company, the status of the rating agency, and others.
 
 On the Russian market, the impact of credit rating upgrades and downgrades on stock prices has not been investigated so far. Ongoing studies of other events affecting stock prices show that the market’s reactions are pretty much in line with those of developed markets, despite its immaturity, limited transparency, high volatility, narrowness and low liquidity, as well as the small number of significant events.
 
 In this article, we evaluate the level of efficiency of the Russian stock market and analyse the reaction of stock prices to changes in issuer credit ratings by international rating agencies using the traditional event study methodology in a narrow event window of 31 days over the period 2016–2020 on a sample of 49 public companies. We show that credit rating upgrades do not lead to statistically significant positive abnormal returns. Visual analysis demonstrates that rating downgrades result in substantial negative abnormal returns. This effect varies for financial and non-financial companies and companies with low and high capitalization yet differs from the effects observed for developed markets; nevertheless, these abnormal returns are not statistically significant. Still, there are grounds to conclude that the Russian stock market
 is not efficient in the semi-strong form and is closer in its characteristics to emerging markets, which is important information for investors, as it permits them to develop profitable trading strategies.

A high-frequency analysis of return and volatility spillovers in the European sovereign bond market

Using high-frequency data from the MTS trading platform, we examine return and volatility spillover effects across different maturities in the European sovereign bond market over tranquil and crisis periods. The longer-term benchmark securities of core countries are the largest net volatility transmitters, whereas the shorter-term benchmarks of periphery countries are the leading net receivers of volatility shocks. Moreover, the short-end and the long-end of the yield curve in both regions emerge as the sole net recipients of return spillovers. We note that bonds of periphery countries become volatility spillover transmitters during important macroeconomic events such as credit rating downgrades and financial assistance packages to financially distressed countries.

Data breaches and firm credit risk

Data breaches may affect firms' future performance, financial stability, and risk profiles, thus potentially resulting in increased credit risk. Using firm-level credit ratings and credit default swap (CDS) spreads to proxy for credit risk, we find that data breaches lead to increases in firm credit risk. Firms exposed to data breaches are more likely to experience credit rating downgrades and an increase in the CDS spread of traded bonds. Also, firms who suffer data breaches report lower sales and ROA, experience an increase in financial distress, and conditional on a data breach incident, the likelihood of a future data breach increases. Lastly, these effects are magnified for firms with low interest coverage ratios.

Does soft information determine credit risk? Text-based evidence from European banks

This paper uses a supervised machine learning algorithm to extract relevant (soft) information from annual reports and examines whether such information determines credit risk (as measured by non-performing loans, Ohlson’s O-score, Altman’s Z-score, and credit rating downgrades). The paper also assesses how far both bank- and country-level characteristics influence variations in credit risks both within and between banks across 19 European countries between 2005 and 2017. Based on 1885 firm-year observations, we find that the text-based credit risk (soft) measure explains a substantial portion of the variation in NPLs, O-score, Z-score, and credit rating downgrades. We also find that bank-level characteristics and country-level characteristics are highly important for explaining variations in non-performing loans, O-score, and credit rating downgrades, as compared to Z-score. Overall, our results have implications for firms, regulators, and market participants who are seeking evidence on the credibility of annual reports in conveying relevant information that reflects actual credit risk.

Measuring credit risk using qualitative disclosure

We use machine learning methods to create a comprehensive measure of credit risk based on qualitative information disclosed in conference calls and in management’s discussion and analysis section of the 10-K. In out-of-sample tests, we find that our measure improves the ability to predict credit events (bankruptcies, interest spreads, and credit rating downgrades), relative to credit risk measures developed by prior research (e.g., z-score). We also find our measure based on conference calls explains within-firm variation in future credit events; however, we find little evidence that the measures of credit risk developed by prior research explain within-firm variation in credit risk. Our measure has utility for both academics and practitioners, as the majority of firms do not have readily available measures of credit risk, such as actively-traded CDS or credit ratings. Our study also adds to the growing body of research using machine-learning methods to gather information from conference calls and MD&A to explain key outcomes.