Dynamic Volatility Spillovers and Risk Transmission Between Oil, Gold, and <scp>G7</scp> Markets: A Crisis Perspective
Bibliographic record
Abstract
ABSTRACT This study examines the volatility spillovers and interconnectedness among oil, gold, and G7 equity markets during three distinct periods: calm period (CP), natural health crises (NHC), and war crises (WC). It analyzes daily data from January 2010 to April 2024, utilizing asymmetric BEKK‐GARCH and Time‐Varying Parameter Vector Autoregression (TVP‐VAR) approaches. Our findings reveal significant spillover effects, with oil markets exhibiting stronger negative impacts on G7 equities during crises compared to gold. Notably, oil acts as a net risk transmitter across periods, while gold serves as a defensive and safe‐haven asset, particularly during NHC. The hedging effectiveness analysis indicates that gold‐G7 portfolios offer superior diversification, while oil‐G7 pairs provide cost‐effective hedging strategies, with France emerging as a key reference point. The pairwise net connectedness analysis identifies the USA, Japan, and Italy as primary shock transmitters during WC, while Canada, France, Germany, and the UK primarily function as shock recipients. Time‐varying spillover results highlight increased market interconnectedness during crises, emphasizing the vital role of commodity markets in risk management. These findings provide actionable insights for portfolio managers facing crises, enabling them to design effective hedging and diversification strategies.
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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 | 0.002 | 0.000 |
| 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 | 0.001 |
| 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".