An Analysis of how Financial Ratios of Companies in Turkey Are Affected by National Standards, and IFRS
Bibliographic record
Abstract
Adoption in 2005 of IAS/IFRS by Turkish listed companies resulted in changes in classification, valuation and disclosure of financial items. This paper makes accessible to non-Turkish speakers a detailed investigation of the results from previous ratio analysis studies identified by Balsari & Varan (Balsari & Varan, 2014), in addition to presenting a more extensive analysis than Cengiz (Cengiz, 2014). Eight financial ratios have been analysed before and after implementation of international standards. One set of results compares the periods 2002-2003 with 2005-2006; and the other 2004 with 2005. The companies investigated are substantially the same in both analyses, but different versions of national standards are compared against international standards. Significant differences in average Book Value of Equity per Share are found after implementation of international standards for both sets of comparisons; and for one set only, at a lower confidence level, significant differences are indicated in the leverage ratio. The major contribution of the paper is the analyses of the differences during the pre and post implementation of international standards.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".