The effect of liquidity risk on the performance of banks: Evidence from Jordan
Bibliographic record
Abstract
This study aimed to determine the impact of liquidity risk on financial performance of Jordanian banks, where liquidity risk was measured by (Liquidity ratio, net working capital, cash and investment ratio to total deposits), and financial performance was also measured through the index (return on assets) and the modifying variable (bank size) measured through the natural logarithm of total assets was also added. To achieve the objectives of the study, the analytical quantitative approach was adopted. The study community consisted of all 13 commercial banks listed on the Amman Stock Exchange. All banks in the study community were selected as a study sample using the comprehensive survey method, and the statistical analysis program (SPSS) was used to test the study hypotheses. Based on the results of the statistical analysis, it was found that there was an impact of liquidity risk on financial performance measured by return on assets in Jordanian commercial banks listed on Amman Stock Exchange, and there was an impact for each of (current liquidity ratio, net working capital, cash and investment ratio to total deposits) on financial performance measured by return on assets in Jordanian commercial banks listed on Amman Stock Exchange. It was also found that the size of the bank contributes to modifying the effect of liquidity risk on financial performance measured by return on assets in Jordanian commercial banks listed on Amman Stock Exchange. The study concluded a set of recommendations, the most important of which are: commercial bank administrations should increase interest in exploiting their liquidity within acceptable risk limits to reach optimal ratios for financial performance by balancing the returns to be achieved with the potential risks of such expenses in a way that ensures the positive impact of liquidity risk on the financial performance of those 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".