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Record W2898777749 · doi:10.5539/mas.v12n11p279

Accounting Measurement Revolution and Market Value

2018· article· en· W2898777749 on OpenAlexvenueno aff
Mohammad Aladwan

Bibliographic record

VenueModern Applied Science · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsnot available
Fundersnot available
KeywordsFair valueAccountingMarket valueFinancial ratioBusinessSample (material)Value (mathematics)Financial accountingAccounting information systemFinancial instrumentMark-to-market accountingFinanceStatisticsMathematics

Abstract

fetched live from OpenAlex

The study is aims to examine whether the adoption of accounting measurement of AIS/IFRS standards has resulted in more relevant financial information for decision making or not. This study examines the use of fair value measurement on value of financial instruments to capture if there is any effect on the market value of financial companies. Ohlson (1995) framework has been employed to investigate this relationship. The Jordanian financial sector was the sample for the study during the years from 2012 to 2016. Our study findings, based on the results of correlation and multiple regression analysis showed that, market value of Jordanian financial companies is significantly positively related to financial instruments measured by fair values. The final result assured that; the new accounting measurements methods such as fair values are value relevant for Jordanian financial companiesduring all period of the study.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0010.009
Scholarly communication0.0050.006
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.015
GPT teacher head0.206
Teacher spread0.191 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2018
Admission routes1
Has abstractyes

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