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Record W4412053390 · doi:10.1016/j.gfj.2025.101152

Accounting disclosures and stock price efficiency: Evidence from mandatory IFRS adoption

2025· article· en· W4412053390 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueGlobal Finance Journal · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsUniversity of AlbertaTrent UniversitySimon Fraser University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsAccountingStock priceBusinessStock (firearms)EconomicsMonetary economicsGeography

Abstract

fetched live from OpenAlex

We investigate whether adopting a uniform set of accounting standards impacts stock price efficiency by introducing a novel empirical test imported from the finance literature. Using mandatory adoption of International Financial Reporting Standards (IFRS) as an exogenous shock to the accounting information disclosure environment and employing a difference-in-difference research design, we find that the extent to which stock prices deviate from their fundamental values decreases significantly following the adoption of IFRS. In cross-sectional tests, we further observe that the impact of IFRS adoption on stock price efficiency is more pronounced in countries with lower accounting quality prior to IFRS adoption and in those with substantial differences between their domestic Generally Accepted Accounting Principles (GAAP) and IFRS. Overall, our study contributes to the literature by empirically examining a fundamental aspect of the IFRS mission statement—whether IFRS adoption enhances financial market efficiency.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.222
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.003
Open science0.0010.001
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 head0.009
GPT teacher head0.233
Teacher spread0.224 · 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