How do economic policy uncertainties affect stock market volatility? Evidence from <scp>G7</scp> countries
Bibliographic record
Abstract
Abstract This study explores the dynamic and frequency spillover characteristics between economic policy uncertainty (EPU) and stock market realized volatility (RV) in G7 countries. We apply the monthly data of country‐specific economic policy uncertainty indices and realized volatility to calculate the directional spillover indicator. Then we use a Fourier transformation to calculate the frequency of spillovers to study the duration of the spillover effect. We find that the spillover effect of EPU on stock market volatility is relatively large in the U.S., Japan and Canada, and has certain regional similarities. EPU has longer spillover effects on the stock markets of France, Germany and Italy, which is strongest over 3–18 months. Finally, important economic events such as the financial crisis and the Brexit, increased EPU spillover level and lasting time. We provide the dynamic and frequency spillover characteristics between EPU and the stock market in G7 countries, making this study useful for international asset allocation and risk management.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".