Energy-related uncertainty and stock market volatility: Evidence from the wealthiest economies in the world through the GARCH-MIDAS approach
Why this work is in the frame
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Bibliographic record
Abstract
This study aims to analyze the effect energy-related uncertainty has on the volatility of the stock markets of 18 developed and developing countries ranking among the wealthiest according to their GDP. The study focuses on understanding how EUI influences market dynamics and volatility patterns across different economies. Using the GARCH-MIDAS approach, this research examines stock market indices from January 2003 to October 2022. The analysis reveals that all stock market indices are influenced by EUI. Notably, the S&P-TSX index exhibits the lowest MIDAS weight, indicating that Canada's market volatility is the least affected by EUI. Conversely, the highest MIDAS component weights are observed in the markets of China and the United Kingdom. The EUI shows the greatest influence on the volatility of the Indian and Chinese markets, whereas its influence is minimal on the Brazilian and Canadian markets.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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