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Record W4360592054 · doi:10.5267/j.dsl.2023.2.005

The effect of audit quality as a moderator on the relationship between financial performance indicators and the stock return

2023· article· en· W4360592054 on OpenAlexvenueno aff
Yazen Oroud, Mohammad Almashaqbeh, Hamed Ahmad Almahadin, Abdulrahman Hashem, Marwan Altarawneh

Bibliographic record

VenueDecision Science Letters · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBanking, Crisis Management, COVID-19 Impact
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessStock (firearms)Stock exchangeModerationQuality auditCash flowAuditGrowth stockAccountingFinanceRestricted stockStock market

Abstract

fetched live from OpenAlex

This study investigates how audit quality moderates the effect of financial performance indicators on the stock returns of Amman Stock Exchange-listed firms (ASE). The panel data analysis selected the data of 95 ASE-listed firms from 2013 through 2021. This analysis demonstrates a significant inverse relationship between a company's book value and its stock returns. A statistically negative relationship was observed between cash flow, dividends per share, and stock return. The empirical results of this study confirm the moderating influence of audit quality in the relationship between financial performance and stock return. Firstly, auditor's fees have a significant impact on the relationship between firm stock returns and EPS, BV, DPS, and cash flows (CFO). The size of the auditing firm moderates the relationship between company stock returns and EPS, DPS, and the CFO, but not with book value (BV). The auditor's opinion moderates the relationship between business stock returns and EPS, BV, and DPS but not the relationship between firm stock returns and cash flows (CFO). The study suggests that regulatory bodies like the Companies Control Department (CCD) and ASE should make sure that local audit firms in Jordan improve their audit quality to be on par with the Big 4 audit firms in order to improve their financial performance measures and stock returns.

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)0.011
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.202
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.051
GPT teacher head0.327
Teacher spread0.276 · 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

Citations10
Published2023
Admission routes1
Has abstractyes

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