Amélioration de la méthodologie de construction de la courbe des taux sans risque dans la zone UEMOA
Bibliographic record
Abstract
Dans la zone de l’Union économique et monétaire ouest-africaine (UEMOA), la construction d’une courbe des taux sans risque est un objectif pour les décideurs publics. En effet, elle permet d’accompagner les mutations réglementaires actuelles, ainsi que le processus de développement du marché financier régional (MFR). En s’appuyant sur les conclusions de Gbongué et Planchet (2015) et Gbongué (2019), nous proposons une nouvelle méthodologie de construction de la courbe des taux sans risque, adaptée aux particularités de cette zone, dans l’optique de réduire les erreurs d’estimation de la valeur théorique des obligations souveraines. Notons qu’elle s’appuie sur les fondamentaux du modèle de Nelson et Siegel, dans le but de faciliter la prévision de cette courbe dans le futur.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".