LIQUIDITY MANAGEMENT AND FINANCIAL PERFORMANCE OF DEPOSIT MONEY BANK PERFORMANCE IN NIGERIA
Bibliographic record
Abstract
This study investigates the impact of liquidity management on performance of deposit money bank in Nigeria. The study made use of ex-post facto research design. Secondary data were sourced on dependent as well as independent variables employed by the investigation were sourced from the reported annual accounts of fourteen (14) chosen DMBs for a period of 15 years, (2009-2023) which was downloaded from the Nigerian Group Exchange (NGX). Dependent variable was financial performance measured using Return on Assets while input variable was liquidity management measured using debt to equity ratio: loan to deposit ratio and liquidity coverage ratio. Firm size was employed as control variable. sourced was analyzed in three stages preliminary, model estimation and post estimation test using panel data regression on -View version 12. The outcome of the evaluation established that equity to debt ratio significantly and negatively impacted ROA, loan to deposit ratio negatively and insignificantly impacted ROA while liquidity coverage ratio negatively and weakly impacted ROA as revealed by the testing of hypothesis at five percent level of significance. The study concluded that the interaction between liquidity management and financial performance of selected financial institutions in Nigeria is complicated. Considering this fact, it was suggested that deposit money banks should adopt liquidity management policy that will make them to achieve efficiency and effectiveness with attention on: liquidity, debt to equity, loan to deposit as well coverage ratios
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.002 | 0.002 |
| 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".