Mind the Gap: Undercollateralization in the Global and Canadian OTCD Markets
Bibliographic record
Abstract
We provide estimates of the collateral gap in the global and Canadian OTCD markets. Using the latest available data as of December 31 2011, it is estimated that current exposures after netting are $3.9T globally and $71B in Canada. The estimated amount of available collateral after correcting for re-hypothecation in each market is $767B and $48B, respectively. Thence, the current gap in variation margins stands at $3.1T globally and at $23B in Canada. The initial margin that would be required to centrally clear OTCD is estimated at $4T globally and $104B in Canada. The rate of collateralization has increased globally, but specially in Canada. In 2001, 92% of global and 72% of Canadian current exposures were undercollateralized; currently, the figures are 80% for global and 30% for Canadian current exposures. The high level of collateralization and the lack of re-hypothecation could make the Canadian market more resilient to systemic shocks. Further, it is likely that the upcoming regulatory reforms will have a more subtle impact on Canadian banks than on banks elsewhere.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".