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Record W4312510101 · doi:10.24036/jkep.v3i2.13599

Pengaruh Variabel Makroekonomi Terhadap Return Saham Sektor Keuangan di Indonesia

2021· article· en· W4312510101 on OpenAlexaboutno aff
Nadia Etri Ningsih, Idris Idris

Bibliographic record

VenueJurnal Kajian Ekonomi dan Pembangunan · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Analysis and Corporate Governance
Canadian institutionsnot available
Fundersnot available
KeywordsStock exchangeEconomicsInflation (cosmology)Stock (firearms)Exchange rateMonetary economicsInflation rateQuarter (Canadian coin)Financial sectorError correction modelFinancial systemEconometricsInterest rateFinanceCointegrationGeography

Abstract

fetched live from OpenAlex

The purpose of this study was to determine the effect of macroeconomic variables on stock returns in the financial sector in Indonesia. The indicators of macroeconomic variables studied were world gold price, exchange rates, inflation, an economic growth. This study uses secondary time series data from 2005 first quarter to fourth quarter 2019. The research data analysis method used is multiple linear regression analysis and Error Correction Model (ECM). The result oh this study indicate that : (1) the world gold price has a negative effect on the stock return of the financial sector in Indonesia; (2) the exchange rate has a negative effect on the stock return of the finacial sector in Indonesia; (3) inflation has a negative effect on stock return for the financial sector in Indonesia; (4) economic growth has a negative effect on the stock return of the finacial sector in Indonesia.

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)0.001
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 score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.013
GPT teacher head0.194
Teacher spread0.181 · 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
Published2021
Admission routes1
Has abstractyes

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