Small Is Beautiful? A Comparison of Major and Minor Credit Rating Agencies Credibility
Bibliographic record
Abstract
The events linked to the subprime crisis undoubtedly damaged the reputation of credit rating agencies (CRAs), at least in the short and medium-term. In this paper, we intend to gauge the extent of that reputational damage by examining the reaction of the market to rating actions. Using a standard event study methodology, we measure the abnormal return of stock prices in the three-day window centred on the announcement day during the period November 2003 – November 2013. Our theory is that the market reaction to downgrades, upgrades and credit watches is lower – after the crisis – than it used to be due to a lack of trust in the neutrality and reliability of the rating agencies. We expect the phenomenon to be more pronounced for the three major CRAs – Moody’s, Standard & Poor’s and Fitch – who had more direct involvement in the scandal. For the minor players, the impact of the crisis is potentially twofold. On one side, they may have suffered from a general mistrust of the rating industry. On the other side, they may have benefited from a higher level of attention from investors in search for a cross-check of opinions.The evidence strongly supports the theory of a lower market reaction to rating announcements, especially for the three major agencies. The abnormal returns of equity prices in an event window of a rating action are significantly lower after the crisis than they were before, after considering various explicative factors relating to the features of the announcement and the market conditions in terms of volatility. In line with previous literature on the topic, we find that, due to the “certification” role that many regulations grant to rating agencies, the abnormal return is stronger when the valuation is near to the border between investment and speculative grade. As a consequence, where the certification role is prevalent, there is no difference in the market reaction to announcements before and after the crisis. Conversely, the cumulative abnormal return is significantly lower after the crisis when there is no “regulation-induced” trading and the market investors’ behaviour is predominantly guided by the faith put in the informative content of the rating.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".