Estimation of physical intensity models for default risk
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Bibliographic record
Abstract
Abstract The estimation of physical intensity processes in the context of default risk is investigated here. Using data from Moody's Corporate Bond Default Database, a term structure of default probabilities for different rating classes is constructed each year from 1970 to 2001. Two specifications used for modeling the dynamics of the (risk‐neutral) intensity process in the bond‐pricing literature are then examined empirically: the Ornstein–Uhlenbeck and square‐root cases. The results reveal that the Ornstein–Uhlenbeck case is not an adequate modeling alternative with a rejection of this specification in five out of seven credit classes and nonsignificant mean reverting behavior for all credit classes. The square‐root case obtains better results with four credit classes out of seven for which this specification cannot be rejected and significant mean reversion parameters in many cases. © 2008 Wiley Periodicals, Inc. Jrl Fut Mark 29:95–113, 2009
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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 | 0.000 |
| 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 | 0.000 |
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 it