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Record W1640100711 · doi:10.5539/res.v7n7p429

Investigation of the Effects of Capital Structure on Value of Listed Companies in Tehran Stock Exchange

2015· article· en· W1640100711 on OpenAlexvenueno aff
Ali Faez, Kalantari Soheila

Bibliographic record

VenueReview of European Studies · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsStock exchangeEconometricsEarnings per shareBusinessLeverage (statistics)Panel dataMultivariate statisticsCapital structurePopulationDividendStatisticsEconomicsFinanceMathematics

Abstract

fetched live from OpenAlex

The objective of present study is to investigate the effects of capital structure on the value of listed companies in Tehran Stock Exchange. The statistical population of present study consisted of listed companies in Tehran Stock Exchange during 2009-2013 and the sample size was equal to 113 companies selected after applying criteria-filtering technique and elimination of outliers and irrelevant observations. In the present study, earnings per share, ratio of dividends per share, fixed assets turnover ratio, current ratio and financial leverage are considered as independent variables to investigate their effects on value of companies. Compiled data as well as panel data are used as fixed effects are supposed. The results of data analysis of different companies through multivariate regression showed 95 percent level of confidence.

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)0.001
metaresearch head score (Gemma)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.053
GPT teacher head0.255
Teacher spread0.202 · 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

Citations2
Published2015
Admission routes1
Has abstractyes

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