Foreign exchange markets, climate risks and contextual news: An intraday analysis
Bibliographic record
Abstract
This paper examines the dynamics of the foreign exchange market, focusing on the impact of macroeconomic, climate risk, and COVID-19 pandemic-related news on currency returns and volatility. Our findings show that prior to the pandemic, currency returns were mainly driven by macroeconomic news, but the onset of COVID-19 shifted attention to pandemic-related news. Vaccine-related announcements consistently increased volatility across markets, reflecting heightened uncertainty. Additionally, climate risk was found to strengthen the four major currencies relative to the US dollar. Finally, the study highlights context-specific effects, with certain indicators losing relevance while others gained prominence during the pandemic. • Climate risks lead to higher exchange rate volatility. • Countries with high exposure to climate change risks experience currency depreciation. • Before the pandemic, currency returns are primarily influenced by macroeconomic news. • The pandemic crisis shifted focus towards pandemic-related news.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| 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) | 0.001 | 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".