The effect of internal risks on the performance of Jordanian commercial banks
Bibliographic record
Abstract
This study mainly aimed to examine the effect of internal risks on the financial performance of the Jordanian commercial banks. The study sample comprised the entire commercial banks that are included in the Amman Stock Exchange (ASE) spanning the period from 2009 to 2019. The study formulated four hypotheses, which are related to the effects of liquidity risk and leverage risk on the bank’s performance, proxied by ROA and ROE. Based on the results, liquidity risk did not have a significant effect on both ROA and ROE, while leverage risk did not have a significant effect on ROA, but it did on ROE. It can thus be concluded that the use of financial leverage should be taken into consideration because of its negative influence on the banks’ financial performance, specifically on the shareholders’ returns. It is recommended that future studies examine the effect of additional risk types, like credit risk and operational risk on the performance of banks.
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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 | 0.001 | 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 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".