Bibliographic record
Abstract
This paper introduces two semi-Markov-modulated short rate processes and discusses the pricing of a zero-coupon bond. Specifically, a semi-Markov-modulated Hull-White (HW) model and a semi-Markov-modulated Cox-Ingersoll-Ross (CIR) model for short-term interest rates are proposed. Under the semi-Markov-modulated HW model, the mean-reverting level and the volatility of short rate process are modulated by a continuous-time, finite-state, semi-Markov chain. Under the semi-Markov-modulated CIR model, only the mean-reverting level is modulated by the semi-Markov chain. Using forward measures, stochastic flows of diffeomorphisms and fundamental matrix solutions of linear matrix differential equations, semi-analytical approximate formulas for the bond price are obtained under the two short rate processes. The formulas are of semi-Markov-modulated exponential affine forms. Numerical studies, comparisons and sensitivity analyses are provided and discussed.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".