Effects of New Financial Reporting Standards on Value Relevance–A Study about Turkish Stock Markets
Bibliographic record
Abstract
Financial statement information that make the users to evaluate their decisions is value relevant. This paper aims to determine the value relevance of financial statement information in Turkish stock markets during the period of 1997-2011 by Ohlson Model (1995) and separate regressions. Starting from 2003, new regulations about financial reporting standards became effective. Consolidation and inflation accounting were put into action in 2003 annual financial statements. Afterwards in 2005, the revised translation of International Financial Reporting Standards (IFRS) was applied. And finally in 2008, one by one translation of IFRS named as Turkish Financial Reporting Standards (TFRS) became effective. So, we also aim to test whether the acceptance of new financial reporting standards made improvements on value relevance of accounting information or not in Turkish stock markets. Our results reveal that earnings and book values both together and separately are significantly value relevant. The explanatory power of book values are higher than the explanatory power of earnings. After new reporting standards, there is an increase in the value relevance of earnings and book values together and this increase is mainly due to the increase in the value relevance of book values.
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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 | 0.007 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".