THE BANK CRISIS FINANCIAL RATIOS : A comparative research of the UK and Sweden during 2006-2010
Bibliographic record
Abstract
The credit crunch that started the 9th of August 2007 is generally viewed as the most significant crisis to affect the financial markets and the global economy since the 1930s.The UK financial sector was heavily hit by the crisis which resulted in a dry up in lending and left a black hole in the British banks‟ finances. During the last quarter of 2010 the GDP shank unexpectedly with 0.5 percent from the third quarter which created concerns about going back into the recession. Contrarily, for Swedish economy 2010 was an impressing year with an unexpected GDP growth of 7, 3 percent in the last quarter.The purpose of this study is to analyse how the finance crisis has affected the leading banks‟ performance within the two countries and see whether the differences in values can explain the difference in GDP growth during the last quarter of 2010. The analyse is performed through a financial ratio analysis of the different banks.The final results of the research indicates to that the Swedish banks have been more profitable, have had a more secure and higher quality of lending and more capacity to lower cost related to income than the British banks. The more distinctive negative influence is mostly based on the larger amount of credit losses the British banks had to experience which contributed to their significant decrease in earnings per share which created scepticism on the credit market followed by a severe slowdown in consumption and in GDP growth. Since the credit losses never got to same levels in Sweden as in the UK the scepticism of the Swedish banking system did not affect the reduction in credit use and house prises to the same extent and GDP growth could recover back to normal levels sooner than in the UK.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".