Introduction
The role of credit rating agencies (CRAs) in assessments of credit risk has grown as capital has flowed away from conventional bank credit and into the financial markets. The CRAs are now responsible for a wider variety of topics. Today’s CRAs do not just rate conventional long-term debt problems; they also rate a wide range of debt products. Increased focus is being paid to the credit market interface by market players. Due to the publicity surrounding default crises like Enron, WorldCom, and Parmalat, equity investors now consider default risk a significant factor. However, because of the severe losses experienced by investors, doubts have been cast on the reliability and value of credit ratings. This thesis aims to contribute new insight into the relationship between credit worries and their impact on stock returns. Our study focuses on unusual stock returns around the time of a report’s publication to see if there is a correlation to changes in creditworthiness. Equity investors are the primary focus of this investigation of the credit rating system in order to uncover the factors that may be linked to investors’ perceptions of risk and the equity markets’ subsequent returns.
The thesis takes this approach to shed light on the mechanisms underlying a possible correlation based on verifiable characteristics and ascertain whether or not credit risk indicators correlate with return tendencies in equity markets. Although the link between credit risk and bond returns is clear, it is not as evident as the link between credit risk and stock prices. The effect of credit rating changes on stock prices after their release has been the subject of multiple studies. The results, based mainly on information from the United States, are not totally definitive. However, according to the vast majority of studies, the announcement reaction to a downgrade is consistently more significant than that for an upgrade.
Ratings on bonds serve the apparent objective of helping investors and issuers save money by eliminating unnecessary research and bridging any existing knowledge gaps. CRAs not only claim to carry out these duties but also to have access to confidential information that plays a role in the ratings they assign. As a result, the market should not be aware of all the reasons for credit rating downgrades when they are announced. Since stock investors are influenced by new information about an issuer’s performance, it is logical to expect that credit rating changes will affect more than simply the performance patterns of debt markets. These trends are essential for a broader set of market participants, including the issuer’s residual claims.
In this dissertation, we investigate the two main aspects of the announcement effect to comprehend the effect of credit risk management value changes on stock returns. The extent to which the market has expected the occurrence is an evident component in the existence and size of any announcement effect. As a second point, it is claimed that changes in the relevance and significance of the underlying information of the rating change for shareholders can primarily account for variances in announcement impacts. By tying its conclusions to the dynamics of the credit rating process and employing an original sample, this thesis contributes to the existing literature on the link between credit risks and equity returns. Through this method of analysis, we can clearly describe a complex relationship by dissecting it along two main axes. This deepens our comprehension of the inter-individual variations and the different outcomes that may result from upgrades and downgrades.
Credit ratings are based on the assumption that they can reliably predict the probability of credit losses owing to nonpayment, late payment, or insufficient payment. It can incur a credit loss if the issuer cuts its projections for future cash flows. Default probability and expected loss magnitude are the two main factors that credit rating agencies like Moody’s and Standard & Poor’s consider when deciding an issuer’s creditworthiness. Standard & Poor’s AAA is their top rating, whereas Moody’s Aaa is their top rating for creditworthiness. Bonds with ratings lower than BBB- or Baa3, indicating significant speculation and credit risk levels, are considered “non-investment grade.” The CRAs quickly differentiate between credit ratings and buy/hold/sell recommendations equity and fixed income experts make. The credit rating agency’s (CRA) opinion on an issuer’s creditworthiness, not investment advice.
The role of credit ratings for bond and equity markets
Generally, there is negligible or nonexistent information asymmetry between the issuer and the investors in publicly offered bond offers. In this respect, the CRAs could be essential to the long-term health of the public debt markets. Since they are well-versed in information collection and possession of sensitive data, credit reporting agencies (CRAs) facilitate borrowers’ access to the debt markets. The term “signaling” describes the act of communicating new information to others. It would be inefficient for individual investors to pay the money necessary to eradicate informational disparities, leading to the collapse of many debt securities markets if this function were removed. Instead of incurring the costs of directly communicating with the market, potential issuers would do better to finance themselves with ordinary bank loans. In addition to their signaling role, CRAs are widely believed to have a licensing role. This role would involve the formalization of a highly qualified credit risk opinion. Credit rating coverage is typically a prerequisite for an issuer to win over investors and regulators. Credit-related information may also be of interest to stock traders. There is a chance that credit ratings are not as crucial to the functioning of stock markets as commonly believed. However, the signaling function of CRAs may also help reduce informational asymmetry in the equity markets.
For the rating mechanism to work, CRAs must continue to be seen as reliable, unbiased sources of information. More and more people are talking about this now. To give just one example, the CRAs had a difficult go of it after the collapse of American utilities giant Enron. Up until a month before it failed, Moody’s and Standard & Poor’s gave the company their highest possible “investment-grade” rating. After hearing of the downgrade, Reuters quoted investors saying, “I do not see why anyone still pays attention […].” The scary part is that new finance laws give rating companies more power (Financial Times, 30 November 2001). Increased attacks on CRAs may be related to the increased significance of credit ratings brought about by the de-intermediation of financial markets. Due to increased competition, major CRAs may be tempted to take advantage of the industry’s inherent conflicts of interest. The announcement effect on stock returns is expected to be most strongly influenced by the amount of new information of importance to shareholders provided by the credit rating event.
Literature Review
Numerous studies have used event-study approaches to examine the impact of credit-rating changes on stock returns. Afik et al. studied how changes in credit ratings affect bond and stock market investors (2014). The study found neither market reacted favorably to news of upgrades or stable ratings. Emawtee and Robert (2014) looked at the capital markets of Australia and Japan to learn more about the relationship between credit risk and stock performance. Stock performance was found to be positively correlated with higher levels of promotion, as discovered by the study.
According to Jones and Marquis (2013), who examined the relationship between stock performance and rating movements using data from 43 US banks over 12 years, rating changes tend to occur when companies either gain or lose market share. Results showed that downgrades had a significant negative correlation with abnormal returns, while upgrades and downgrades had a significant positive correlation with abnormal returns in the post-announcement period. Sachdeva et al. (2013) used information from 12 Indian financial institutions to examine the dynamics of stock return fluctuations in response to changes in credit ratings. There was a clear pattern showing that upgrades significantly impacted stock returns more than downgrades. At the time of the upgrading, the returns shown by the larger banks are higher than those shown by, the smaller banks.
In 2009, Calderoni et al. studied the long-term effects of rating actions on the stock markets of 12 European countries. The -statistic, the t-test, and the event study all found that downgrades significantly impact stock returns more than upgrades. Doron et al. (2009) examined the monthly returns of all companies listed on US stock exchanges to investigate why a high-risk firm generates low returns rather than high ones. It was found that the returns from investing in a company’s shares are more significant if the stock has a higher credit rating. Research conducted by Winnie and Kam in 2008 examined the impact that changes in ratings had on the stock returns of Chinese companies. Results from the study indicated that agency ratings are helpful and that markets react positively to news of downgrades.
Adam et al. investigated how rating changes influenced stock prices in the Australian market (2007). According to the findings, both an upgrade and a downgrade significantly impact the price of a company’s stock following their announcement, with the latter having a more profound impact on smaller businesses. Linciano (2004) examined the impact of 299 rating changes on Italian stock market swings. Ratings were more helpful to institutional investors seeking growth in their assets than individual traders. Li et al. analyzed the effect of rating changes on the Iranian stock market (2004). A cross-multivariate regression test and an event-based analysis determined that only downgrades contribute meaningfully to the stock market.
Empirical studies of the impact of rating changes often analyze stock price changes before, during, and after the announcement of the change. They conduct their investigation using a method inspired by “event studies.” If a rating change reveals relevant new information, the market should react after its announcement. Rating agencies rely primarily on publicly available information to determine ratings, so rating modifications should not affect business prices. The efficient market hypothesis implies that stock prices already represent all relevant information.
Existing research “provides only sporadic and rather inconsistent evidence on this problem,” write Dichev and Piotroski (2001), explaining why the effect of rating adjustments has not been investigated more thoroughly. Because researchers can choose their models and statistical tests, the literature has not been able to agree on an optimal technique for event studies. Due to variations in study length, selection criteria, rating agencies, anomalous return measurements, sample filters, and subsequent applications, academic studies on the topic have produced contradictory conclusions.
Academic research has found that downgrades result in significant financial losses while upgrades do not. It was not until Vassalou and Xing (2003) reported two anomalies that could not be explained from the standpoint of individual investors’ conduct in financial markets that this discovery became firmly established as mainstream in the literature. To begin, the market should respond similarly to downgrades and upgrades if ratings truly offer new information to the market. Therefore, downgraded stocks should have a positive abnormal return, as investors require more significant returns to compensate for the higher risk they assume when purchasing a downgraded stock. The authors were compelled to look into this phenomenon because of how frequently it occurred. After conducting statistical analyses and cross-sectional regression investigations, they determined that the anomalies were from using a method to calculate the anomalous return that neglected a biasing component. It is crucial to incorporate credit risk into the study, as it was demonstrated to be a strong predictor of stock returns.
Differences in findings were traced back to the absence of the credit risk level variable in the analysis. While Vassalou and Xing laid the groundwork, two other substantial investigations added to it (2003, 2004). According to Norden and Weber (2004), the magnitude of the anomalous return depends on the rating both before and after the change. When dealing with anomalies, Jorion and Zhang (2006) take a more forceful stance than Norden and Weber (2004), who find that downgrades and upgrades have similar effects on stock returns regardless of the previous rating, and instead develop a study that places a premium on the importance of the pre-change rating variable.
The default likelihood index (DLI) displays inverted V behavior around the date of the notification of a risk rating revision, as per studies by Vassalou and Xing (2003). The company’s actions since the announcement are explained in light of this. They also note that the size of the inverted V changes depending on the pre-announcement rating, suggesting nonlinear behavior concerning the risk rating. An increase or decrease in stock price is proportionate to the disparity between the old and new ratings for a company’s shares. This is why a second channel is required for the return analysis. This helps even out the positive and negative consequences of rating changes. When using the prior rating level as a measure of credit risk, all of these authors seem to have arrived at the same conclusion: businesses with a higher risk are expected to generate greater profits. Therefore, a bias may help explain why downgrades have impacted pricing significantly. Upgraded firms often have lower credit risk. Thus the anomalous return from a downgrade is smaller for them (Campbell & MacKinlay, 1997). It is because there is a bias in rating distributions toward downgrades for businesses already doing poorly. In contrast, downgrades may seem more important since companies are more prone to conceal bad news than good. It has been claimed that credit rating agencies are more vigilant in their search for indicators of deterioration in credit quality than they are in their search for recoveries since it would be more damaging to their reputation if they failed to predict serious credit difficulties (for instance, as in the subprime crisis).
Contemporary authors frequently suggest new models for event studies that attempt to account for the problem by challenging existing research methods (as in Vassalou and Xing, 2003, 2004). Additionally, most papers have used the conventional event study methodology as described by Campbell, Lo, and Mackinlay (1997), which includes the following issues: the use of cumulative abnormal return (CAR); a period that encompasses not only a period after the event has occurred but also a period around or prior to the event (although the specific choice is arbitrary); and little attention to choosing the reference portfolio to measure the abnormal return. However, Barber and Lyon (1996) investigated the empirical power and specification of statistical tests used in event studies to identify anomalous stock market returns. They concluded with revisions to enhance the significance of the tests. It is recommended that the buy-and-hold (BHAR) measure be used instead of the more common capital-gains-adjusted return (CGAR) measure of abnormal return because “CARs are biased predictors of BHARs,” which can lead to incorrect conclusions and an inaccurate portrayal of the value of a stock investment over time. Second, investors should employ portfolios sorted by firm size and book-to-market ratio to condition the anomalous return rather than basing measurements on a reference portfolio (such as the market index), which can be skewed in three ways (due to listing, rebalancing, and skewness).
These changes were made in response to Dichev and Piotroski’s (2001) work. They produced one of the most critical studies in the current literature, with a focus on the long term, which serves as the most excellent reference for the development of this study. Freitas and Minardi’s (2013) research stands out because it evaluates Latin American countries individually using the conventional CAR method while covering the entire region. Brazil had a significant role in this study as a big contributor to the sample size. As a result, theirs is the closest to our story, but in a little different direction, than the ones we have found.
Effects of Credit Rating Announcement/Declaration
EE (2008) categorized the responses of American Latin stocks to reports of credit rating changes into three categories. Some of the many elements that determine a credit rating are business management, Legal Matters, and Discrepancy Between Public and Confidential Data. In their study of credit rating announcements in China, Poon and Chan (2008) found that the influence of accreditation was unevenly distributed across the board. Credit rating changes were also observed to increase manufacturing firms’ negative nonstandard returns, regardless of the firms’ sizes.
Between 1990 and 2000, Elayan et al. (2003) analyzed the effect of credit rating releases on New Zealand stock prices. The findings established significant reactions, including credit-rating announcements. Analysis of 299 rated Italian firms by Linciano (2004) between 1991 and 2003 revealed that degraded firms saw poor and negative anomalous returns the day before and the day after the rating declaration. Ratings’ impact on stock returns was studied by Jorion and Zhang (2006), who employed a metric called the Cumulative Abnormal Return to do so (CAR). Frames from the year before (year=-1) and the year after (+year=+1) were compared on the announcement’s effective declaration date. When comparing companies that have been upgraded and degraded, it was found that the upgraded companies typically had a much higher and more positive CAR. Goh and Ederington (1993) found that downgrades associated with changes in firms’ leverage do not inform the capital market of any new negative information, whereas downgrades associated with a deteriorating financial outlook do.
Process of Credit Rating
The credit rating agency (CRA) can commence its rating process after it has received approval from the issuer. Then, a group of analysts is selected to work on the rating, with one of them taking charge. The working group sits with the issuer’s executive management to discuss these factors. After the primary research is finished, a rating committee reviews the primary analyst’s suggestion. It takes most of the rating committee’s 5-10 credit experts to approve the proposed rating opinion. Issuers have the right to contest their assigned rating but must provide supporting documentation. The Committee will decide whether to uphold or reject the appeal by a simple majority vote (Campbell & MacKinlay, 1997).
In most areas outside the United States, disclosing the rating is entirely voluntary. A press release detailing the issuer’s rating decision is available at the issuer’s discretion. Issuers of public debt can choose to keep tabs on their ratings for more than a year if they so desire. The exact process used to assign ratings initially is used to decide whether or not those ratings should be changed. Rating trends and the application of the Watchlist are also given significant consideration. The rating outlook represents the CRA’s opinion on the likely direction of any rating action in the medium term. It can be either positive (signifying an upward trend) or negative (indicating a decline). The 18-month outlook is provided. There must be consensus from the rating committee or the senior analyst with support from the managing director before an updated forecast can be released (Emawtee & Robert, 2014). If new information calls into question the accuracy of the current rating, the item will be transferred to the Watchlist. The Watchlist message will include whether the issuer is being examined for an upgrade, downgrade, or no change in direction. Typically, a decision on whether or not to change the rating is made within 90 days.
Performance of Credit Rating
Trust in the rating process and CRAs’ motivations to provide timely information depend critically on this ability to examine the evidence-based performance of credit ratings. There is historical evidence to back up the claim that CRAs provide accurate assessments of relative credit risk. One method of gauging success in credit risk measurement is to examine the correlation between credit ratings and pricing or credit risk in financial markets. Poorer credit grade debt securities have been found to continuously experience bigger spreads in the market (Sarig & Warga, 1989). These figures represent this range of dates, beginning in February 1985 and ending in September 1987. Because CRAs are not primarily concerned with assessing absolute credit risk, the implied default probabilities associated with the various credit ratings may shift over time (Cantor et al., 1994). Over the long run, credit ratings can be employed as absolute risk indicators because they are projected to maintain a high degree of consistency within each credit rating group.
Summary
It has been noted that the notification effects on equity returns associated with credit rating modifications might be affected by several aspects of the credit rating process. Both dimensions are connected to several different elements. However, some elements are more relevant to the study and can be tested and quantified more easily. There are visual elements with clear theoretical implications for the effect connected with the expectation of the rating event, such as the rigidity of credit ratings, the opinions of rating agencies regarding future developments, and the inclusion of companies on their Watch lists. The most significant and direct impact on the information’s relevance for shareholders comes from the criteria that trigger a rating update and the incentives for CRAs to give timely and accurate information. Some remaining space in both dimensions may be crucial even though their relevance is more difficult to prove scientifically.
Announcement Effects
According to the findings of an event study, the original sample saw a significant unexpected announcement impact for downgrades on the day of the event and the trading day that followed. During this same period, no tremendous reactions to improvements were seen. Therefore, H1 is only partially supported, specifically, that changes in credit ratings are associated with unusual shifts in stock price. Hypothesis 4’s prediction that upgrades and downgrades have varied impacts on share prices is also confirmed. Despite the sizeable response to downgrades, the finding may be contested since the observed effect on the day of the announcement is not statistically significant. The magnitude of the reaction is also low.
If the market is efficient, the announcement of a credit rating downgrade should provide price-relevant information to equity markets. Here, we get confirmation of the prediction of the information content hypothesis. However, the significant unusual pre-announcement effect for such events shows that not all relevant information becomes available to the market at the moment of the announcement but rather in the protracted period leading up to the announcement. Therefore, the results imply that not all data provided by CRAs should be treated as secret. The market appears to have absorbed some but not all of the price-relevant information prior to the rating change, indicating that the downgrade decision was not reached purely based on non-public information. The released information may uncover potential advantages of credit rating agencies (CRAs) in gathering, analyzing, and interpreting public data.
The effect’s significance supports this unusual announcement effect for downgrades, and the size is smaller after the announcement than before. This indicates that the appropriate pricing information for a particular rating event is associated with the rating event itself. It was discovered that the abnormal response to enhancements was relatively minimal, likely due to the offsetting effect of the transfer of wealth. Nonetheless, generalizability constraints prevent us from separating this effect from others that may be attributable to information content or signaling. However, the effect on shareholders in the downgrading sample can be inferred to be the inverse of that expected due to the absence of a wealth redistribution effect.
Market prices and information availability
In an efficient economy, the actual price of an asset would represent all known information about that asset. Some empirical evidence suggests that this streamlined approach is inefficient. The fact that insider traders have been found to make above-average profits, for instance, supports the argument that market prices may not always reflect all available information about a company’s worth. The market’s unusual reaction to an increase in a company’s credit rating may indicate that the rating agency has access to material information that has not been made public (Emawtee & Robert, 2014). Semi-strong market efficiency occurs when prices adjust after the dissemination of new information. Three theories can explain announcement effects under the assumption of semi-strong market efficiency: the information content hypothesis, the wealth redistribution hypothesis, and the signaling hypothesis.
Information content hypothesis
The integrative theoretical hypothesis proposed by Zaima and McCarthy (1988) states that the CRA and the market have different levels of information. In light of this, investors may find information about changes in a company’s credit rating to be instructive. Two different explanations address the hypothesis. Some have argued that there is a lag between when something is announced and when it hits the market and that CRAs can only access publicly available data. The security credit rating should not affect its price much if the market is reasonably efficient. More evidence for this view comes from Holthausen and Leftwich’s (1986) argument that credit rating organizations do not maintain a close check on businesses and that rating movements are often connected to new debt issuance. Rating agencies say Wakeman (1984) and Kaplan and Urwitz (1979) are more likely to represent just publicly available information since they are more concerned with certification than research.
There is also the possibility that CRAs can access material that is not public knowledge. If information collecting is costly, CRAs may be among the most cost-effective sources available. They are well-versed in scouring the medical literature for information on obscure conditions and other mysteries that might otherwise remain hidden from the public. Specifically, Ederington et al. (1984) identify two causes for this phenomenon. First, there are economies of scale associated with collecting and analyzing this data. Second, there is a potential for an agency issue if managers make the information they provide to rating agencies public. The hypothesis postulates that stock prices would adjust whenever a company’s credit rating was altered.
Wealth Redistribution and Information Relevance
The results of this study lend support to the hypothesis that investors will experience anomalous announcement effects when a rating upgrade occurs only if the underlying cause for the change is relevant to them. Substantial empirical evidence and various theoretical factors underpin this view. To begin, a change in the issuer’s profitability or market position is more likely to be linked to altered projections for the firm’s future cash flow generation than a change in the capital structure. Since bondholders face a higher degree of risk, any redistributive benefits should be muted, and the effect on stockholders should be unaltered. According to the credit rating subsample, the announcement effect was small because of shifts in leverage. Alteration in the distribution of wealth is possible if an increase in credit risk does not lead to a decrease in expected future cash flows. Because they soften the blow of potential adverse reactions, this may explain the lack of a backlash to these observations. Instead, a more significant reaction can happen even if wealth redistribution effects are not there.
Investors are more likely to care about updated expectations for financial performance than the news of changes in capital structure. This is because there is now more data available to analyze financial performance. Therefore, the absence of reaction to downgrades may be due, at least in part, to their lack of significance for shareholders. Moreover, the fact that different grading explanations lead to different outcomes proves this. The conclusion drawn from the regression analysis of downgrades shows that the scope of the evaluation of changes in economic performance if the variable is relevant and how large it is created is much larger than the one relating to the leverage employed. This coherence between performance and relevance arguments is also reflected in the negative sign of the financial coefficient.
Differential Relevance due to Rating Class and Transition
Credit reporting agencies (CRAs) deploy rating models whose designs indirectly influence the information related to rating adjustments. Because various issuers have varying credit quality, the relevance to shareholders must vary accordingly. Consistent with the findings of cross-sectional studies, issuers with lower ratings are more vulnerable to the downgrade announcement effect. Because of this, it is clear that, as anticipated by the rating models’ design, changes in financial risks have a more significant impact on shareholders than changes in business-related risks. These definitions, while helpful, are relatively comprehensive and leave much to the judgment of the CRAs. Given this, we can only conclude that the CRAs’ weighting of input characteristics explains why changes in ratings between lower ratings impact shareholders more.
How Changes in Credit Ratings Affect Investment Returns
The big event window of 14 days shows no statistically significant influence of an upgrade in a business’s credit rating by Moody’s on the company’s stock price throughout the whole dataset (2006-2015). It would appear that the market only reacts strongly four days or more after the rating change announcement, but robustness studies across shorter event periods fail to corroborate these findings. Results from announcements of credit rating downgrades show that Moody’s credit rating releases always cause a significant market reaction. By doing robustness checks over T-1 to T+1 and T-3 to T+10, Moody verifies these results. When looking at the other two rating agencies, S & P and Fitch, the results of downgrades reveal that announcements have little impact on asset values. The results from each of the three-time frames for the event are the same.
It turns out that before the global credit crisis, rating modifications made by the major rating agencies had little effect on the values of assets. There is no statistically significant difference between the three rating agencies regarding the impact of a change in credit ratings across the main event window of 14 days. The three-day robustness test demonstrates that stock prices respond strongly to positive rating revisions from S&P and Fitch. The same paradox is true for adverse changes in S&P and Moody’s ratings from the intermediate time frame T3 to T+3, but with a more significant event window. The number of upgrades and downgrades over this period is negligible. As can be seen from the contrasting effects of rating agency announcements, market volatility has increased in the years following the global credit crisis. Investors who place the most weight on Fitch’s rating pronouncements were the most sensitive to the shift. The results demonstrate that the announcement of an upward change substantially impacts the abnormal returns of securities during all three event periods. Both shorter event windows after Fitch’s announcement of downgrades saw significant results.
Statements made by Moody’s have shown that their followers only react strongly to downward changes in their ratings. These results are consistent with previous research showing that companies aim to spread the good news as soon as possible so that investors are not caught off guard by credit rating increases (Chen et al., 2001; Bae et al., 2006; Alsakka & Gwilym, 2012). According to the findings, S&P rating announcements do not signal new information to the market. The only significant influence on securities prices is shown in response to higher rating revisions over the brief three-day event window employed as a robustness check.
Similar findings were observed by Bissoondoyal-Bheenick and Brooks (2015). They discovered that announcements of credit rating downgrades significantly impacted markets in Australia and Japan, whereas announcements of upgrades had a negligible impact on returns. In line with the idea that optimistic news about a company is disseminated more quickly, rating upgrades do not tell investors anything new. Looking at the times before, during, and after the global credit crisis is also inconclusive. Except for the robustness check over the entire three-day event window (T – 1 to T + 1), the results for the two years leading up to the GFC are generally consistent with those for the entire sample. These differences appear both in positive and negative changes in credit ratings.
Consistent with previous studies and the tests for the entire sample, we demonstrate that declines in credit ratings lead to sizable shifts in security prices for the period after the global credit crisis. This study’s results during the event window T3 to T+10 differ from those of earlier research and the time before the GFC, suggesting that investors may need up to 10 days to react positively to a credit rating improvement. Before and after the global credit crisis, the market appeared more sensitive to announcements of changes in credit ratings by individual rating agencies (2006-2007 and 2009-2015, respectively). Except for the 14-day downgrade window that followed the global credit crisis, announcements of changes in Fitch’s credit ratings significantly impact the value of securities. Investors place high importance on Fitch’s credit rating revisions and use them to guide their spending and saving habits (Emawtee & Robert, 2014). Furthermore, downgrade statements by Moody’s have a significantly more significant impact on security prices than upgrading ones. They indicate that individuals relying on Moody’s credit ratings have started interpreting the downgrade announcement as unique and relevant information. When looking at the effect of rating change announcements across rating classes, it is clear that the market reacts strongly to upgrades from speculative to investment grade. This is true across all three event windows studied. Nonetheless, consistent with earlier research findings, we find a sizable effect for downward rating revisions inside the investment-grade category.
Conclusion
By providing an independent evaluation of an issuer’s ability to repay its debts, credit ratings let all market participants, especially investors, decide whether or not to back that issuer with their capital. The influence of credit rating upgrades and downgrades, as well as the behavior of investors in such circumstances, were analyzed. By employing the event study method and t-tests, an analysis of the impact of rating changes on the companies was made. This study demonstrates that positive and negative rating changes have a material impact on the stock performance of investors. These announcements have a more significant impact on the day of the announcement and for some time later. In light of this, it is clear that rating announcements have a significant impact on the stock prices of firms, both now and in the future.
References
Adam C, Luke G and Anthony R J (2007). “The Impact of Rating Changes in Australian,” Pacific-Basin Finance Journal, pp. 1-17.
Afik Z, Feinstein I and Galil K (2014), “The (Un)informative Value of Credit Rating Announcements in Small Markets,” Journal of Financial Stability, pp. 66-80.
Barber, B. M., & Lyon, J. D. (1996). Detecting abnormal operating performance: The empirical power and specification of test statistics. Journal of Financial Economics, 41(3), 359-399.
Calderoni F, Colla P and Gatti S (2009), “Rating Changes Across Europe”, Working Paper, Bocconi University.
Campbell, J. Y., Lo, A. W., & MacKinlay, A. C. (1997). The econometrics of financial markets (2nd ed). New Jersey: Princeton University Press.
Cantor, R. and Packer, F., (1994). “The credit rating industry,” Federal Reserve Bank of New York Quarterly Review.
Dichev, I. D., & Piotroski, J. D. (2001). The long-run stock returns following bond rating changes. Journal of Finance, 56(1), 173-203.
Doron A, Tarun C, Gergana J and Alexander P (2009). “Credit Ratings and the Cross-Section of Stock Returns,” Journal of Financial Markets, pp. 469-499.
Ederington, L.H., and Goh, J.C, (1993). “Is a bond rating downgrade bad news, good news, or no news for stockholders,” Journal of Finance, Vol. 48, No. 5.
Ederington, L.H.; Yawitz, J.B., and Roberts, B.E., 1984, “The informational content of bond ratings,” NBER Working Papers, No. 1323.
Emawtee B B & Robert B (2014). “The Credit Risk-Return Puzzle: Impact of Credit,” Pacific’Basin Finance Journal.
Financial Times, 30 November 2001, “Agencies come under scrutiny.”
Freitas, A. de P. N., & Minardi, A. M. A. F. (2013). The impact of credit rating changes in Latin American stock markets. BAR – Brazilian Administration Review, 10(4), 439-461.
Holthausen, R.W. and Leftwich, R.W., 1986, “The effect of bond rating changes on common stock prices,” Journal of Financial Economics, Vol. 17, Iss. 1.
Jones E & Marquis Q M (2013). “The Stock Market Reaction to Changes to Credit Ratings of US-Listed Banks,” Centre for Finance and Investment Discussion Paper Series DP2013-AEF03, British Accounting and Finance Association (BAFA) Scottish Area Group Conference, September.
Jorion, P., & Zhang, G. (2006). Information effects of bond rating change: The role of the rating prior to the announcement. The Journal of Fixed Income, 16(4), 45–59.
Kaplan, R.S. and Urwitz, G., (1979). “Statistical models of bond ratings: a methodological inquiry,” Journal of Business, Vol. 52, Iss. 2.
Li X H, Visaltanachoti N and Charoenwong C (2004). “Market Reaction to Credit Rating Announcements in the Irish Stock Markets.”
Linciano N (2004). “The Reaction of Stock Prices to Rating Changes,” available at www.ssrn.com.
Moody’s Investors Service, 2005, “Moody’s default research.”
Moody’s Investors Service, 2005, “Default risk services database.”
Norden, L., & Weber, M. (2004). Informational efficiency of credit default swap and stock markets: The impact of credit rating announcements. Journal of Banking & Finance, 28(11), 2813-2843.
Sachdeva S, Gupta A and Kapoor A (2013), “Monitoring Abnormality in Returns Around Credit Rating,” Journal of Commerce and Management Thought, Vol. 4, No. 3.
Sarig, O. and Warga, A., (1989). “Some empirical estimates of the risk structure of interest rates,” Journal of Finance, Vol. 44, No. 5.
Vassalou, M., & Xing, Y. (2003, January). Equity returns following changes in default risk: New insights into the informational content of credit ratings. EFA 2003 Annual Conference Paper, p. 326. Retrieved from https://papers.ssrn.com/sol3/papers.cfm?abstract_id=413905
Wakeman, L.M., (1984). “The real function of bond rating agencies,” The Modern Theory of Corporate Finance, New York, McGraw-Hill Inc.
Winnie P P and Kam C C (2008). “An Empirical Examination of the Informational,” Journal of Business Research, Vol. 61, No. 7 (July), PP- 790-797.
Zaima, J.K. and McCarthy, J., (1988). “The impact of bond rating changes on common stocks and bonds: tests of the wealth redistribution hypothesis,” The Financial Review, Vol. 23, No. 4.
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