How do economic policy uncertainties affect stock market volatility? Evidence from <scp>G7</scp> countries
Why this work is in the frame
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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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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 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 it