Bibliographic record
Abstract
The paper examines the effect of monetary policy statement shocks on exchange rates. I use Google's Natural Language tools to measure and track changes in the sentiment of FOMC and ECB post-meeting statements. The results reveal a negative relationship between the dollar's value and FOMC statement shocks. Investors sell (buy) the dollar when the sentiment of the FOMC statement is more positive (negative) than the previous one. This negative relationship could be explained by the special status of the U.S. dollar as a safe-haven currency and the significant effect of U.S. monetary policy on other countries' macroeconomic fundamentals. The value of the euro is positively related to ECB statement shocks. The size of the exchange rate response to statement shocks is comparable to that of term structure shocks. There is no material difference between the response of exchange rates in conventional and unconventional times. Statement shocks affect the exchange rates through the information channel.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".