The impact of economy policy uncertainty and oil price shocks on G20 banks’ stock performance: Wavelet coherence and non-parametric causality in quantiles approach
Bibliographic record
Abstract
This study employs nonparametric causality-in-quantiles and wavelet coherence techniques to examine the impact of economic policy uncertainty and oil price variations on bank stocks in twelve prominent global economies. The results reveal that the effects of both economic policy uncertainty and oil prices on bank stock values vary significantly across countries and over time. Notably, during stress periods, we observe an inverse relationship between economic policy uncertainty and bank stocks in multiple countries, namely, Brazil, Canada, France, India, Russia, and the USA, with Japan exhibiting a particularly strong and long-term adverse correlation. Similarly, the influence of oil prices is primarily observed during crisis periods, but it demonstrates a substantial co-movement with bank stocks across the sample countries except Brazil. Our empirical analysis holds valuable implications for policymakers, bankers, investors, and portfolio managers.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".