Liquidité du marché des actions et rendements des fonds mutuels en temps de crise : évidence canadienne
Bibliographic record
Abstract
Cet article porte sur la relation entre les rendements des fonds mutuels canadiens et la liquidité du marché des actions. Nous cherchons spécifiquement à documenter comment cette relation a évolué au cours de la période entourant la crise de liquidité qui a secoué le monde financier en 2008. Ces travaux sont importants puisque d’une part, les fonds mutuels sont des véhicules d’investissements très présents dans l’économie et d’autre part, la liquidité des marchés financiers est un catalyseur du risque systémique. Nos résultats montrent que la prime d’illiquidité traditionnellement observée au sein des fonds mutuels avant la crise – dont dans cette étude – a donné lieu à une prime d’illiquidité au plus fort de la crise et a modifié l’évaluation de ces fonds par la suite.
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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 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 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".