An Analysis of the Performance of the Canadian Banks during the Global Financial Crisis
Bibliographic record
Abstract
Several studies have evaluated the effect of the credit crunch on banks’ performance in different countries. In this study we intend to find its impact on Canadian banking system. We aim to analyze the Canadian banks’ performance from year 2006 till 2013 to find weather they remained profitable during years 2008 and 2009 or not, as well as find their strengths and weakness points of banking system. For this reason we have chosen 8 big banks of Canada. ROA and ROE have considered as profitability measure’s factors. The CAMEL model has identified as powerful and reliable to evaluate the efficiency of banks operation and its parameters correlation with profitability variables. We have two dummy variables to assess the banks’ performance during years 2008 and 2009 separately. All the collected data were displayed by the Panel Data and analyzed through Regression model. The empirical analysis provides us an effective inside regarding bank performance and the impact of the financial credit crisis on the Canadian banking system. ÖZ: Çeşitli çalışmalarda farklı ülkelerdeki kredi krizinin bankaların performansına etkilerini değerlendirilmiştir. Bu çalışmada da amaç Kanada bankacılık sistemi üzerindeki etkisini incelemektir. Kanada bankalarının 2006 ile 2013 yılları arasındaki performanslarını analiz etmeyi, 2008 ve 2009 yıllarında karlı kalıp kalamadıklarını, bankacılık sisteminin güçlü ve ve zayıf yönlerine de işaret ederek bulmayı, hedefliyoruz. Çalışmada Kanada’nın 8 büyük bankası ele alınmıştır. Karlılığı ölçmede ROA ve ROE faktörleri kullanılmıştır. CAMELS modeli, bankaları operasyonun etkilediğini ve karlılık değişkenleri ile parametrelerinde korelasyon değerlendirmek için güçlü ve güvenilir olarak belirlenmiştir.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".