Asymmetries and State Dependence: The Impact of Macro Surprises on Intraday Exchange Rates
Bibliographic record
Abstract
The impact of news surprises on exchange rates depends in principle upon a number of factors including the state of the economy, institutional setting and nature of the expected policy response. These characteristics may lead to state-contingent asymmetric responses to news. In this paper we investigate the possible asymmetric response of intraday exchange rates (5-minute intraday JPY/USD) to macroeconomic news announcements during a very unusual period--Japan during 1999-2006 when the money market interest rate was effectively zero. We may think of this period as a natural experiment consisting of an institutional setting when interest rates may rise but not decline, thereby constraining both endogenous policy reactions to news and private market expectations. Asymmetric responses to news, to the extent that they are important in exchange rate markets as they are in equity markets, would seem particularly likely to be evident during this period. We consider several ways asymmetric responses may be manifested and linked to macroeconomic news during the zero-interest rate period. We assess whether the intraday exchange rate responds differently depending on whether the news is emanating from Japan or the U.S.; we consider the state of the business cycle; and we distinguish between good and bad news.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.027 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".