International currency markets and the <scp>COVID</scp>‐19 pandemic
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract We find that quantifying COVID‐19 pandemic shocks is critical to understanding international currency market returns. Scaled by population, shocks from between‐country differences in the number of weekly COVID‐19 deaths are informative in predicting exchange rate returns. Following Alfaro et al. (2020), we estimate the expected number of COVID‐19 deaths based on an exponential model and use it to construct two pandemic shocks that measure the unanticipated number of deaths on a weekly basis and the time‐varying correction of forecast provided new information from the previous week. We document negative impacts of COVID‐19 propagation on currency returns. In addition, we find that the government response, in particular fiscal and monetary stimulus packages, can help mitigate negative effects of COVID‐19 on currency returns. Our findings are robust to country‐specific pandemic measures, window sizes of the exponential model, and the choice of forecast model.
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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 | 0.005 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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