The Analysis Of Comments Received By The BIS On Principles For Sound Liquidity Risk Management And Supervision
Bibliographic record
Abstract
The market turmoil that began in mid-2007 re-emphasized the importance of liquidity to the functioning of financial markets and the banking sector. In June 2008, the Basel Committee of the Bank for International Settlements (BIS) released a consultative document on Principles for Sound Liquidity Risk Management and Supervision. Interested parties were invited to provide written comments by the end of July 2008. As a result, the Committee received many comments for publication by 30 different commenters. Our analysis first indicates that comments were formulated on each of the 17 principles discussed in the consultative document. Second, comments were also made in each of the five separate defined areas of focus covered by the 17 principles. Third, the results of our analysis reveal that opinions on different principles differed the most when commenters were separated into four distinct categories: banking trade associations, regulatory supervisors, individual financial institutions, and others (consultants, academics, accounting associations, and financial information providers). Last but not least, the results of the study indicate that commenters’ opinions, both within a category and between categories, differed the most in the two following defined areas of focus: measurement and management of liquidity risk and public disclosure of quantitative information on liquidity risk management.
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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 | 0.042 | 0.296 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 0.009 |
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".