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Record W2144434537 · doi:10.17722/ijrbt.v5i2.344

The Moderating Impact of Individual Ownership on The Relationship between Dividend Yield and Ex-dividend Day Excess Return

2014· article· en· W2144434537 on OpenAlexvenueno aff
Babak Barkhordar, Rubi Ahmad

Bibliographic record

VenueInternational Journal of Research in Business and Technology · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsDividend yieldYield (engineering)DividendBusinessDividend policyEconomicsEconometricsMonetary economicsFinanceMaterials science

Abstract

fetched live from OpenAlex

This study investigates the moderating impact of individual ownership on the relationship between dividend yield and ex-dividend excess return. Our sample includes US listed companies for years 2002 to 2010. A cross-sectional regression analysis is done to reveal the moderating impact of individual ownership. Our findings show that there is a positive relationship between dividend yield and ex-dividend day excess return in line with tax clientele theory. We also found that the relationship between dividend yield and the ex-dividend day excess return is positively moderated by individual ownership. These findings reveal that the positive relationship between dividend yield and ex-dividend day excess return stems from individual investors’ dividend tax misgiving in line with tax clientele theory. Moreover, we found a negative relationship between corporate size and ex-dividend day excess return that supports the short selling theory. We conclude that tax-induced dynamic trading theory is the premier justification of ex-dividend day pricing as the mixture of both tax clientele and short selling theories.

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)0.004
metaresearch head score (Gemma)0.006
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 score0.033
Threshold uncertainty score0.732

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.137
GPT teacher head0.356
Teacher spread0.220 · 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

Citations1
Published2014
Admission routes1
Has abstractyes

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