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Record W2011334835 · doi:10.1002/asmb.640

Strong dependence in the nominal exchange rates of the Polish zloty

2006· article· en· W2011334835 on OpenAlexaboutno aff
Luis A. Gil‐Alana, Mike Nazarski

Bibliographic record

VenueApplied Stochastic Models in Business and Industry · 2006
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsnot available
Fundersnot available
KeywordsPound (networking)Liberian dollarMean reversionEconomicsLong memoryEconometricsExchange rateShock (circulatory)Financial economicsMonetary economicsVolatility (finance)FinanceComputer science

Abstract

fetched live from OpenAlex

Abstract We examine the nominal exchange rates of six currencies (Canadian, Australian and U.S. dollars, euro, Japanese yen and U.K. pound) against the Polish zloty by means of statistical techniques based on unit roots and other long memory processes. We use both parametric and semiparametric methods for estimating and testing integer and fractional orders of integration at the long run or zero frequency. The results show that unit roots are likely to occur in relation with the U.S. and the Canadian dollars, the Japanese yen and the U.K. pound. However, for the Australian dollar and the euro, this hypothesis is rejected in favour of smaller degrees of integration, implying mean reversion in their behaviour. Thus, for the former currencies, in the event of an exogenous shock affecting the exchange rates, strong policy actions must be required to bring the variables back to their original levels. On the other hand, for the Australian dollar and the euro, there exists less need of action since the series will return to their levels sometime in the future. Copyright © 2006 John Wiley & Sons, Ltd.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.630
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.079
GPT teacher head0.232
Teacher spread0.153 · 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 designTheoretical or conceptual
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

Citations6
Published2006
Admission routes1
Has abstractyes

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