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Record W2898693385 · doi:10.24149/gwp305

The Exchange Rate Effects of Macro News after the Global Financial Crisis

2017· article· en· W2898693385 on OpenAlexaff
Yin‐Wong Cheung, Rasmus Fatum, Yohei Yamamoto

Bibliographic record

VenueFederal Reserve Bank of Dallas, Globalization and Monetary Policy Institute Working Papers · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsUniversity of Alberta
FundersTokyo Center for Economic Research
KeywordsMacroFinancial crisisExchange rateEconomicsSet (abstract data type)Monetary economicsFinancial economicsMacroeconomicsComputer science

Abstract

fetched live from OpenAlex

We explore whether the exchange rate effects of macro news are time-and state-dependent by analyzing and comparing the relative influence of US and Japanese macro news on the JPY/USD rate before, during, and after the Global Financial Crisis. A comprehensive set totaling 40 time-stamped US and Japanese news variables and preceding survey expectations along with 5-minute indicative JPY/USD quotes spanning the 1 January 1999 to 31 August 2016 period facilitate our analysis. Our results suggest that while US macro news are now more important than before the Crisis, the influence of Japanese macro news has waned to the point of near-irrelevance. These findings are of particular importance to exchange rate modeling of the New Era.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.332
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.034
GPT teacher head0.255
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2017
Admission routes1
Has abstractyes

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