MétaCan
Menu
Back to cohort
Record W3124675386

Seasonality of exchange rates in Ghana

2015· article· en· W3124675386 on OpenAlexaboutno aff
John Barnes Evans, Tawiah Vincent Konadu

Bibliographic record

VenueResearch in Drama Education The Journal of Applied Theatre and Performance · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Analysis and Corporate Governance
Canadian institutionsnot available
Fundersnot available
KeywordsSeasonalityLiberian dollarDepreciation (economics)Exchange rateAutoregressive integrated moving averageEconomicsQuarter (Canadian coin)EconometricsSeasonal adjustmentRegression analysisStatisticsGeographyMathematicsVariable (mathematics)Monetary economicsTime seriesFinanceEconomic growth
DOInot available

Abstract

fetched live from OpenAlex

The seasonality of Ghanaian economic activities such as agriculture, consumption, money supply among others which affect exchange rate gives the impression that, the Cedi – US Dollar rate also follows a particular pattern within the year. Using quarterly interbank Exchange rate data from 2000 to 2014, sourced from Bank of Ghana,this study has established the quarterly behaviour of the Cedi against the US Dollar. To achieve this, both statistical analysis and econometric model including trend, F – Test, K – Test and regression were computed with the aid of X-12 Census ARIMA program provided by the US Census Bureau. Whiles the trend analysis suggest seasonal depreciation of the Cedi with peak in the fourth quarter, the regression results indicates statistically insignificant average mean difference between the quarters. However, the moving seasonality test showed a cyclical pattern of seasonal frequencies evolving from year to year. The general conclusion we established from the study is that depreciation of the Ghana cedi to the dollar follows a moving seasonality with a pattern constantly repeated year to year

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.067
GPT teacher head0.315
Teacher spread0.248 · 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 source (direct Gemma or distilled Codex), 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
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueResearch in Drama Education The Journal of Applied Theatre and PerformanceSame topicFinancial Analysis and Corporate GovernanceFrench-language works237,207