Bibliographic record
Abstract
This thesis describes the joint probability distribution of defaults in two, three and four dimensions. In particular, default as defined by Merton and Black and Cox using analytical and simulated Monte Carlo approaches. Our analytical approach in a Merton setting, utilizes the multivariate normal to compute the joint probability distribution in any dimension. In a Black-Cox setting, analytical solutions are defined in specific dimensions, therefore we rely on a simulated approach. The precision of our simulated approaches are evaluated using 104, 107 and up to 107.5 paths 1. We use our results to compare the probability of defaults in both settings as well as tail dependence, portfolio value and value at risk. Tail dependence is evaluated in two and three dimensions with ρ=0.3 and ρ=0.9. We define covariance parameters in four dimensions; "normal" and "crisis" market conditions, to evaluate portfolio value in a credit and market portfolio and value at risk.
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How this classification was reachedexpand
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) | 0.001 | 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) | 0.001 | 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 teacher head, 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".