Macro-financial models of Canadian dollar interest rate swap yields
Bibliographic record
Abstract
This paper analyzes the dynamics of Canadian dollar-denominated (CAD) interest rate swap yields. It applies autoregressive distributive lag (ARDL) models, using monthly time series data, to estimate the effects of the current short-term interest rate and other relevant macro-financial variables on interest rate swap yields. It shows that the current short-term interest rate is a crucial driver of the swap yields of different maturity tenors. Similar patterns of interest rate swaps denominated in other hard currencies, such as the US dollar, euro, British pound sterling, and Japanese yen, have been discerned in previous empirical research testing the Keynesian hypothesis, which maintains that the current short-term interest rate has a decisive influence on the long-term interest rate. Thus, the findings of this paper lend additional support to the Keynesian hypothesis by showing that the same pattern holds for CAD interest rate swap yields. The results obtained in the paper can be useful for portfolio managers, corporate leaders, and policymakers.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".