The Difference between Stock Prices before and after Implementation of International Financial Reporting Standards
Bibliographic record
Abstract
Following the trend of capital market globalization, many countries have begun to use unified accounting standards. The resulting, financial statements are consistent and can thus attract foreign investment, and reduce the costs of multinational companies with regard to preparing financial statements. After the implementation of the International Financial Reporting Standards (IFRS), the earnings and book value of the shareholders’ equity are more relevant to stock prices, and this is also the case in Taiwan. Because the financial statements are different before and after incorporating IFRS, this has had a significant influence in the Taiwanese financial industry. This study analyzes and explains the impacts of the earnings and book value of equity on stock prices. We take a sample of financial firms in the years 2012 and 2013 for empirical research, and the results show that the earnings per share and book value of equity have a positive and significant impact on stock prices, with the earnings per share being most significant. The results also support the hypothesis proposed in this paper: There is a decline in the value relevance of earnings, but an increase in the value relevance of book value of shareholders’ equity, after implementation of IFRS. This implies the implementation of IFRS has valuable relevant information for capital market investments.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".