Market Price of Risk Analysis from Three Major Industrial Countries on the Stability of the Brennan-Schwartz Model
Bibliographic record
Abstract
At any given time, market price of risk must be the same for all derivatives and it is linked in par-ticular to interest rate. The Brennan-Schwartz model is one of the stochastic differential equations for the interest rate under the risk neutral probability measure. To estimate parameters of this model, it is required that the real data which are collected in the real world in which the distribution of interest rate process is under the actual probability measure. Therefore, parameter estimators are obtained by changing the measure which is determined by the market price of risk. Hence, market price of risk must make the Brennan-Schwartz model becomes stable, which is important to describe resistance of the model to the perturbation in the initial state or parameters of the model. This paper aims to analyze the market price of risk from three major industrial countries: USA, Japan, and Canada. This analysis can be used as a guideline to decide that the interest rate of these three major industrial countries can be modeled as Brennan-Schwartz model. ");} // --> activate javascript
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".