Prediction of default probability in banking industry using CAMELS index: A case study of Iranian banks
Why this work is in the frame
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Bibliographic record
Abstract
This study examines the relationship between CAMELS index and default probability among 20 Iranian banks. The proposed study gathers the necessary information from their financial statements over the period 2005-2011. The study uses logistic regression along with Pearson correlation analysis to consider the relationship between default probability and six independent variables including capital adequacy, asset quality, management quality, earning quality, liquidity quality and sensitivity of market risk. The results indicate that there were no meaningful relationship between default probability and three independent variables including capital adequacy, asset quality and sensitivity of market risk. However, the results of our statistical tests support such relationship between default probability and three other variables including management quality, earning quality and liquidity quality.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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