Are the separate financial accounts also relevant? Assessing those accounts reported by listed European entities
Bibliographic record
Abstract
The International Accounting Standard (IAS) 27 should be used in the preparation of separate financial statements (SFS) for entities with securities traded on regulated markets within the European Union (EU) that adopt International Financial Reporting Standards (IFRS). This research aims to assess the value relevance of SFS. Additionally, it also analyses the value relevance of the interests under IAS 27 reported therein. It uses documental analysis as a technique and researches archival as a method, with entities from the major indices of EU countries as a research sample. Linear regression models are used for data analysis. The findings indicate that both the SFS and those interests influence the entities’ share prices. As far as the authors’ knowledge, this research solves a gap in the literature by assessing the value relevance of interests reported in the SFS and the SFS itself, which have not been reaching the same attention by researchers compared to studies with similar purposes but focusing on the consolidated financial statements. As a contribution, this study can benefit standard-setter bodies and local regulators in understanding the usefulness of SFS for stakeholders’ decision-making by stressing the relevance of those accounts, and the material items reported therein.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.103 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".