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Record W2594698115 · doi:10.5539/res.v9n2p1

The Relationship between Capital Structure and Financial Performance in the Companies Listed in Abu Dhabi Securities Exchange: Evidences from United Arab Emirates

2017· article· en· W2594698115 on OpenAlexvenueno aff
Anas Ali Al-Qudah

Bibliographic record

VenueReview of European Studies · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsAbu dhabiCapital structureProfitability indexBusinessDebtFinanceDebt ratioReturn on capitalReturn on equityFinancial systemMonetary economicsAccountingEconomicsFinancial capitalCapital formationProfit (economics)

Abstract

fetched live from OpenAlex

This study aimed to examine the relationship between capital structure and financial performance in the firms listed in Abu Dhabi Securities Exchange (ADX), Profitability Ratios were used to express of the financial performance, and the Debt Ratio was used to express the Capital Structure. A random sample from the companies listed in ADX was taken to achieve the objective this study, it consisted of 48% of all companies in this financial market, and the study period extended from 2008 to 2015. The researcher used Statistical Package for the Social Sciences (SPSS), to analyze the study hypotheses, using ANOVA, model summery and coefficients for the study variables. And the results of this study showed that is positive relationship between the capital structure (Debt Ratio) and the Financial Performance (Profitability: Return on Assets) in ADX. And there is a negative relationship when we used the Return on Equity to express for the Profitability with the capital structure. The overall study results showed that there is significant relationship between capital structure and financial Performance in the companies listed in Abu Dhabi Securities Exchange, and the model of this study able to explanation almost 31% from changes happened in the profitability due to the capital structure. This result was consistent with some previous studies.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.420

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.090
GPT teacher head0.293
Teacher spread0.203 · 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.

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

Citations12
Published2017
Admission routes1
Has abstractyes

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