Debt Covenant Violations, Credit Default Swap Pricing, and Borrowing Firms’ Accounting Conservatism
Bibliographic record
Abstract
We investigate the impact of debt covenant violations (DCVs) on credit risk reflected in credit default swap (CDS) spread, and how the two elements, combined together, affect the relation between DCVs and financial reporting conservatism of borrowing firms that are referenced in CDS contracts. We find that DCVs induce a significant increase in CDS spreads during the trading days subsequent to borrowers’ SEC filing dates, indicating increased credit risk of borrowing firms upon DCVs. We also find that borrowing firms’ financial reporting becomes more conservative post DCVs, especially when borrowing firms’ CDS spreads incur large increases and their institutional shareholders play a stronger role of external monitoring. Our finding of increased CDS spreads upon DCVs is consistent with the view that CDS-protected lenders lack incentives to exercise their control rights. To the extent that lenders do not intervene in borrowers’ financial reporting, our finding of increased conservatism suggests that borrowing firms tend to report more conservatively under the influence of other stakeholders such as institutional investors whose equity investment are not protected by credit insurance CDS.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".