Strategic Commodities' Price Risk and Financial Contagion in Oil and Gas Exporting Countries
Bibliographic record
Abstract
This study investigates the occurrence of stock market contagion effects stemming from strategic commodities and the United States (U.S.) equity markets to major oil and gas exporting nations amid the COVID-19 and Russian-Ukraine crises. Employing a multi-factor asset pricing model and risks spillover technique, we scrutinize the sensitivities of market returns to these risk factors and the dynamics of shocks transmission among market sensitivities over time. Our findings reveal that these equity markets generally demonstrate positive and variable sensitivities to the three factors, with Canada, UAE, Kuwait and Saudi Arabia experiencing significant periods of negative response to the gas price factor. Notably, the Russian market exhibited the highest responsiveness to the U.S. factor at the outbreak of the Russian-Ukraine war, whereas the Russian market displays the greatest sensitivity to both oil and gas price risks. The degree of shocks propagation among market sensitivities is about 75.8% and is mainly driver by sensitivities to the U.S. market factor in the energy market, followed by the sensitivity of oil prices to the gas market. Policymakers in these nations should be cautious of potential contagion from the US market and these critical commodities, particularly oil, to mitigate any adverse impacts on their economies.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".