Russia–Ukraine Conflict, Commodities and Stock Market: A Quantile VAR Analysis
Bibliographic record
Abstract
The Russia–Ukrainian war, which began in 2014 and exploded with the invasion of the Russian army on 24 February 2022, has profoundly destabilized the political, economic and financial balance of Europe and beyond. To the humanitarian emergency associated with every war has been added the deep crisis generated by the strong energy and food dependence that many European countries, and not only European, have developed over decades on Ukraine (especially for wheat) and Russia (especially for natural gas). The aim of this article is to verify the existence of a link between the performance of the Eurostoxx index and the price of wheat futures and TTF natural gas, from 25 February 2019 to 28 September 2023. Through a quantile VAR analysis, a link is sought between the Eurostoxx 50 index, and wheat and TTF gas futures prices. Furthermore, the analysis intends to understand whether the presence of such relationship only manifested itself following the war events, or whether it was already present in the market. The analysis carried out also shows that the relationship between the stock market and raw material prices was present even before the conflict.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".