The Determinants of Commercial Bank Profitability in Canada
Bibliographic record
Abstract
This dissertation uses average return on equity (ROAE), the average return on assets (ROAA) and net interest margin (NIM) as an indicator, examines the bank-specific factors and the influence of macroeconomic factors on bank profitability by Canadian Banks in 2011-2018, aimed to explore the underlying determinant of Canadian Banks profits, and tries to find out the relationship between bank profitability and its important determinants. Meanwhile, in order to improve the competitiveness of Banks, this paper combines the important determinants with the risk management framework. The results show that cost efficiency and liquidity are the most important and significant factors in determining bank profitability; Macroeconomic factors, including GDP growth rate and inflation rate, have no significant impact on profitability. The proof of the importance of bank-specific factors provides further enlightenment for the practice of bank risk management.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".