A Framework in Search of an Optimal Margining Policy for Official Institutions: The Canadian Experience
Bibliographic record
Abstract
One of the main outcomes of the global financial crisis has been a series of new regulations imposed on the financial system and specifically on banks. As a result of the changing regulations, bank dealers introduced various “credit” and “liquidity” charges for uncollateralized over-the-counter (OTC) derivatives trades, governed by a one-way or asymmetric credit support annex (CSA), whereby only bank dealers are required to post collateral in favour of official institutions—sovereigns, central banks, government agencies, sovereign wealth funds and supranational institutions—such as the Government of Canada. These charges have sharply increased costs for the government, which, like other official institutions, has been an extensive user of OTC derivatives. In this paper, we propose a framework that official institutions can use to analyze the cost and risk trade-offs among potential margining policies, including moving to a more symmetric CSA versus the prevailing one-way CSAs. Our analysis indicates that, in the case of Canada, moving to a more symmetric CSA results in lower cost and risk for the government relative to the prevailing one-way CSA margining policy, due to the government’s relatively lower funding cost. In fact, all margining policies tested dominate the prevailing one-way CSA prior to 2015. As a result, remaining under the one-way CSA and continuing to transact OTC derivatives is no longer the best policy given the charges levied against the government.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 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".