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Record W3122448865 · doi:10.24149/gwp59

Are the Intraday Effects of Central Bank Intervention on Exchange Rate Spreads Asymmetric and State Dependent?

2010· article· en· W3122448865 on OpenAlexaff
Rasmus Fatum, Jesper Holst Pedersen, Peter Norman Sørensen

Bibliographic record

VenueFederal Reserve Bank of Dallas, Globalization and Monetary Policy Institute Working Papers · 2010
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsIntervention (counseling)Exchange rateCurrencyForeign exchange marketMonetary economicsEconomicsForeign exchangeEconometricsFinancial economicsBusiness

Abstract

fetched live from OpenAlex

This paper investigates the intraday effects of unannounced foreign exchange intervention on bid-ask exchange rate spreads using official intraday intervention data provided by the Danish central bank. Our starting point is a simple theoretical model of the bid-ask spread which we use to formulate testable hypotheses regarding how unannounced intervention purchases and intervention sales influence the market asymmetrically. To test these hypotheses we estimate weighted least squares (WLS) time-series models of the intraday bidask spread. Our main result is that intervention purchases and sales both exert a significant influence on the exchange rate spread, but in opposite directions: intervention purchases of the smaller currency, on average, reduce the spread while intervention sales, on average, increase the spread. We also show that intervention only affects the exchange rate spread when the state of the market is not abnormally volatile. Our results are consistent with the notion that illiquidity arises when traders fear speculative pressure against the smaller currency and confirms the asymmetry hypothesis of our theoretical model.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.178
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.029
GPT teacher head0.240
Teacher spread0.212 · 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.

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

Citations0
Published2010
Admission routes1
Has abstractyes

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