The Effect of Risk Factor Disclosures on the Pricing of Credit Default Swaps
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT This study examines the relation between narrative risk disclosures in mandatory reports and the pricing of credit risk. In particular, we investigate whether and how the Securities and Exchange Commission ( SEC ) mandate of risk factor disclosures ( RFD s) affects credit default swap ( CDS ) spreads. Based on the theory of Duffie and Lando (2001), we predict and find that CDS spreads decrease significantly after RFD s are made available in 10‐K/10‐Q filings. These results suggest that RFD s improve information transparency about the firm's underlying risk, thereby reducing the information risk premium in CDS spreads. The content analysis further reveals that disclosures pertinent to financial and idiosyncratic risk are especially relevant to credit investors. In cross‐sectional analyses, we document that RFD s are more useful for evaluating the business prospects and default risk of firms with greater information uncertainty/asymmetry. Overall, our findings imply that the SEC requirement for adding a risk factor section to periodic reports enhances the transparency of firm risk and facilitates credit investors in evaluating the credit quality of the firm.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it