Duration and Interest Rate Risk for a Binomial Interest Rate Stochastic Process
Bibliographic record
Abstract
Abstract This paper presents duration measures devised for the Ho‐Lee binomial bond‐pricing stochastic process. The returns per dollar from any interest rate sensitive portfolio of securities is illustrated diagrammatically and it is shown that the duration measure is a one‐to‐one indicator of the returns per dollar. The Ho‐Lee process is developed as a special case of the Heath, Jarrow, Morton hypothesis. In cases where the returns per dollar on a portfolio may be negative, there is a positive probability that a financial position or financial institution, for whom these returns can occur, will result in insolvency. The investor or investing institution, by the use of interest rate sensitive derivatives, can control the degree of interest rate risk present in its balance sheet. All of these developments are illustrated in a two‐dimensional geometric presentation. Résumé Les mesures de durée sont crées pour le processus stochastique Ho‐Lee d'estimation d'une obligation bino‐miale. Le rendement par dollar de n'importe quel portefeuille de titres à taux d'intérět instables est illlustré diagrammaticalement et il est démontré que la mesure de durée est un indicateur terme à terme du rendement par dollar. Le processus Ho‐Lee est développé en tant que cas spécial de l'hypothèse Heath, Jarrow, Morton. Dans les cas où les rendements par dollar d'un portefeuille pourraient s'avérer négatifs, il y a une probabilité positive qu'une position ou institution financière, pour qui ces rendements se produisent, se retrouvent insolvables. L'investisseur ou l'institution investisseuse, par l'utilisation de dérivés à taux d'intérěts instables, peuvent contrǒler le degré de risque relié au taux d'intérět présent dans son bilan. Tous ces développements sont illustrés dans une présentation géométrique bi‐dimensionnelle.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".