MétaCan
Menu
Back to cohort
Record W2783587057 · doi:10.5430/afr.v7n2p39

The Impact of Tax Amnesty Announcement towards Share Performance and Market Reaction in Indonesia

2018· article· en· W2783587057 on OpenAlex

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.

venuePublished in a venue whose home country is Canada.
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

VenueAccounting and Finance Research · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Analysis and Corporate Governance
Canadian institutionsnot available
Fundersnot available
KeywordsAbnormal returnAmnestyStock exchangeStock marketEvent studyBusinessStock (firearms)Monetary economicsEconomicsFinancial systemFinanceLaw

Abstract

fetched live from OpenAlex

The Indonesian Government reviewed back the tax amnesty in 2016. Various reactions came up along with the announcement of tax amnesty, the investors did not accept- which led to the announcement of the Tax Forgiveness regulation through the market reactions and stock market performances in Indonesia Stock Exchange. This research is to analyze event study using information based on government-related announcements to show the impact of the new regulation towards stock performance and market reaction. The effect of the announcement will be seen from the changes in stock-prices or stock-returns that provide abnormal returns in the event period as well as market reaction which reflected in trading volume. This research used stock-return data and trading volume from all companies listed in IDX in 2016 and analyzed using the Paired Sample T-Test method. The result of this research shows there are differences among the average of stock-return, average abnormal-return of stock, and stock trading volume before and after the tax amnesty announcement.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.156
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.032
GPT teacher head0.293
Teacher spread0.261 · 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