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Record W2766923807 · doi:10.5430/afr.v6n4p285

The Difference between Stock Prices before and after Implementation of International Financial Reporting Standards

2017· article· en· W2766923807 on OpenAlexvenueno aff
Shu-Ling Hsu

Bibliographic record

VenueAccounting and Finance Research · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsnot available
Fundersnot available
KeywordsEquity (law)International Financial Reporting StandardsBook valueEarningsShareholderBusinessEarnings per shareCapital marketAccountingStock marketEarnings response coefficientFinanceEconomicsCorporate governance

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

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)0.004
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.398
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0010.001
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 head0.030
GPT teacher head0.356
Teacher spread0.326 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2017
Admission routes1
Has abstractyes

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