THE BASEL COMMITTEE PROPOSAL ON RISK-WEIGHTS AND EXTERNAL RATINGS: WHAT DO WE LEARN FROM BOND SPREADS?
Bibliographic record
Abstract
The Basel Committee for Banking Supervision proposed a system of risk weights (the so called “standardised approach”) to measure the riskiness of banks’ loan portfolios. Its ability to adequately reflect risk is empirically investigated in this paper, through an analysis of the economic capital allocations implied in corporate bond spreads. This is based on a unique dataset of issuance spreads, ratings and other relevant bond variables (such as maturity, face value, time of issuance and currency of denomination) including 3,307 eurobonds issued by Canadian, European, Japanese and U.S. companies during 1991-2001. Three main results emerge. First, the spread/rating relationship is strongly significant with spreads increasing when ratings worsen. Second, the estimated spreads per rating class indicate a much steeper risk/rating relationship than the one proposed by the Basel Committee. Finally, no significant difference appears to exist in the spread/rating relation of banks and non- financial firms issuers. Following this empirical evidence, we propose some relevant changes in the standardised approach risk-weights.
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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 | 0.048 | 0.121 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".