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Record W3125101027

Real-Time Effects of Central Bank Interventions in the Euro Market

2007· preprint· en· W3125101027 on OpenAlexaff
Rasmus Fatum, Jesper Holst Pedersen

Bibliographic record

VenueResearch at the University of Copenhagen (University of Copenhagen) · 2007
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Policies and Impacts
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsExchange rateIntervention (counseling)Volatility (finance)Central bankPsychological interventionMonetary economicsForeign exchange marketEconomicsRobustness (evolution)Monetary policyForeign exchangeEconometricsBusinessMedicine
DOInot available

Abstract

fetched live from OpenAlex

This paper investigates the real-time effects of foreign exchange intervention using official intraday intervention data provided by the Danish central bank. Denmark is currently pursuing an active intervention policy under the provisions of the Exchange Rate Mechanism (ERM II) and intervenes on a discretionary basis when considered necessary. Prior participation in ERM II is a requirement for adoption of the Euro. Therefore, our study is of particular relevance for the new European Union member states that are either currently participating in ERM II or expected to do so at a later date as well as for Denmark. Our analysis employs the two-step weighted least squares estimation procedure of Andersen, Bollerslev, Diebold and Vega (2003) and an array of robustness tests. We find that intervention exerts a statistically and economically significant influence on exchange rate returns when the direction of intervention is consistent with fundamentals and intervention is carried out during a period of high exchange rate volatility. We also show that the exchange rate does not adjust instantaneously to the unannounced and discretionary interventions under study. We conclude that intervention can be an important short-term policy instrument for exchange rate management.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.295
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0030.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.1670.013

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 head0.067
GPT teacher head0.278
Teacher spread0.211 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations0
Published2007
Admission routes1
Has abstractyes

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