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Record W4387672778 · doi:10.3390/ijfs11040122

Blockholdings, Dividend Policy, Stock Returns and Return Volatility: Evidence from the UAE

2023· article· en· W4387672778 on OpenAlexaff
Umar Butt, Trevor W. Chamberlain

Bibliographic record

VenueInternational Journal of Financial Studies · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDividendStock (firearms)Dividend policyVolatility (finance)Monetary economicsBusinessEconomicsFinancial economicsFinance

Abstract

fetched live from OpenAlex

This paper examines the relationship between the presence of blockholdings and stock returns and return volatility in the United Arab Emirates. Earlier studies report mixed results for the direction of the relationships across both developed and emerging markets. This study focuses specifically on these relationships in a dividend policy framework. This study further investigates the role of blockholder type by distinguishing between government, individual and corporate blockholders. Our results indicate that blockholder ownership reduces stock return volatility for both non-dividend-paying and dividend-paying stocks, does not impact returns and is not perceived as expropriating the wealth of other investors. We also conclude that the blockholders do not exhibit rent-seeking behavior through the extraction of dividends and investors in UAE firms embrace the role of blockholders and the reinvestment of profits.

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)0.002
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 score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.072
GPT teacher head0.309
Teacher spread0.237 · 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
Published2023
Admission routes1
Has abstractyes

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