Behaviour of Bank Share Prices and Their Impact on National Stock Market Indices: Comparing Countries at Different Levels of Economic Development during Recessionary and Non-Recessionary Periods
Bibliographic record
Abstract
The performance of banks and their effects on the global economy has been of interest to politicians, academicians, businesses and the general public especially in connection with the 2008/09 credit crisis. In particular, the extent to which the bank stock prices affected the national stock market indices in different countries before and during the crisis is unclear. It is also not clear whether the national stock markets of countries at different levels of economic development reacted differently to the crisis. This paper contributes to filling these gaps. It uses regression and correlation analytical techniques in the analysis of the impact and behaviour respectively. The results suggest that the behaviour of most of the stock market indices was similar regardless of the level of economic development. The mean stock market indices were statistically significantly higher before than during the credit crisis. Bank share prices were generally negatively correlated comparing the period before and during the crisis. Some countries were characterised by a few powerful banks that determined the course of the respective national stock market index. This has implications on policy and reveals the intervention points in regulating the performance of stock markets and stabilizing the financial sector.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".