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Record W3134122219

ANALISIS DETERMINAN RETURN SAHAM YANG TERDAFTAR DI BEI PADA MASA TRANSISI COVID-19

2021· article· id· W3134122219 on OpenAlex
Sarah Inesya Anugrah Utami, Alfida Aziz, Jubaedah Jubaedah

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueKonferensi Riset Nasional Ekonomi Manajemen dan Akuntansi · 2021
Typearticle
Languageid
FieldBusiness, Management and Accounting
TopicFinancial Analysis and Corporate Governance
Canadian institutionsnot available
Fundersnot available
KeywordsStock exchangeMarket liquidityStock (firearms)EconometricsQuarter (Canadian coin)BusinessEconomicsMonetary economicsFinanceGeography
DOInot available

Abstract

fetched live from OpenAlex

This research is a quantitative study that aims to determine and analyze the effect of liquidity, company size, and interest rates on stock return in automotive companies and components listed on the Indonesia Stock Exchange in the period of Quarter IV 2020, Quarter I 2020, and Quarter II 2020. This study used 12 companies as samples with the saturated sample method. The analysis technique used in this research is Panel Data Regression Analysis with the help of the E-Views version 10 program. The results of this study indicate that liquidity (current ratio) and firm size (total assets) has no significant effect on stock return of automotive and component companies, while interest rates (BI 7-Days Repo Rate) has significant effect on stock return.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.498
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.026
GPT teacher head0.233
Teacher spread0.207 · 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