Bibliographic record
Abstract
The main result of this paper is the establishment of an analytic formula for the estimation capital requirements of an individual loan. The derived formula, may be considered as a direct analogue to the Basel risk-weight functions for credit risk, first presented in Basel II framework, with the additional advantage of utilizing a lifetime horizon, thus being suitable for IFRS9/GAAP purposes. Essentially, it bridges the gap between Basel and IFRS9 frameworks as: The 1-year horizon incorporated in the Basel PD is extended up to maturity, following the IFRS9 rationale; The notion of unexpected losses, already supplied by Basel Framework, is added to the IFRS9 logic in an analytic fashion. Going one step further, the generalization of the risk variables used in the formula, as Kumaraswamy identically distributed variables, allows for the benchmarking of the total loss of a credit portfolio, with the single knowledge of its current non-performing loans percentage. This conclusion is successfully verified against EBA stress test results for the period 2018-2020.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".