A unified approach to explicit bond price solutions under a time-dependent affine term structure modelling framework
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Bibliographic record
Abstract
The richness and simplicity in the econometric specification of interest rate dynamics are the main motivations why affine term structure models (ATSMs) continue to be popular nowadays. Analytic solutions for bond prices are also available for some cases of these models. With explicit bond price formulae, the estimation of parameters using market data can, in principle, be carried out. In addition, with the appropriate choice of functional forms for the drift and volatility components, certain desirable features of interest rate behaviours (e.g., mean reversion, positive rates, etc.) can be captured. The desirable properties of the family of ATSMs also include the capacity to specify the distribution of the rates, their suitability for Monte Carlo simulation, and the fact that interest rate derivatives are computable from the bond prices and interest rate dynamics in a straightforward manner. It is therefore not surprising that the characterization of ATSMs has been the subject of many previous investigations in interest rate theory.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it