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Record W2108178598 · doi:10.19030/iber.v10i5.4230

Information Content Of Dividend Announcements: An Investigation Of The Indian Stock Market

2011· article· en· W2108178598 on OpenAlexaff
Shania Taneem, Ayşe Yüce

Bibliographic record

VenueInternational Business & Economics Research Journal (IBER) · 2011
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsDividend policyDividendStock exchangeDividend yieldProfitability indexBusinessStock marketEmerging marketsMonetary economicsShare priceFinancial economicsEmpirical researchEconomicsFinance

Abstract

fetched live from OpenAlex

According to the dividend information content hypothesis, dividend changes trigger stock returns because they reflect changes in managements assessment of a firms future profitability. This hypothesis has motivated a considerable amount of theoretical and empirical research. The general procedure used in prior research begins with classifying the dividend change announcement into either favorable or unfavorable. Dividend policy of companies operating in the emerging markets is very different from the widely accepted dividend policies operating in the developed countries. The purpose of this research is to examine the information content of dividend announcements and price movements in the emerging Indian stock market. The paper investigates the information content and market reaction to dividend announcements using data from the developing Indian market. We focus on the information content of dividend policies through the share price reaction of 82 companies in India that are listed in the Bombay Stock exchange.

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)0.000
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 score0.015
Threshold uncertainty score0.458

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.006
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 head0.125
GPT teacher head0.278
Teacher spread0.153 · 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

Citations19
Published2011
Admission routes1
Has abstractyes

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