MétaCan
Menu
Back to cohort
Record W1831433823 · doi:10.5539/ijef.v7n9p50

Stock Market Reaction to Dividend Announcements from a Special Institutional Environment of Vietnamese Stock Market

2015· article· en· W1831433823 on OpenAlexvenueno aff
Quốc Trung Trần, Y Dat

Bibliographic record

VenueInternational Journal of Economics and Finance · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsVietnameseDividendDividend policyStock marketDividend yieldBusinessStock (firearms)Monetary economicsFinancial economicsStock priceEvent studyStock exchangeStock market bubbleInsiderInsider tradingEconomicsFinance

Abstract

fetched live from OpenAlex

Vietnamese stock market is an interesting laboratory to examine the reaction of stock price to dividend announcements due to its taxation regulations. The study employs traditional event study methodology to investigate the impact of dividend announcements on stock prices in a special institutional environment of Vietnamese stock market. The research sample includes 979 dividend announcements made by 233 companies listed on HOSE from 2008 to 2014. Although there is no preferential tax treatment of dividends to capitals gains in Vietnamese stock market, this study finds that dividend announcements lead to positive effects on stock prices and trading volume in the stock market. Although dividend announcements in three clusters including dividend increases, dividend decreases and no change have positive impacts on stock prices, the cluster of increases has the largest effect. Moreover, examining the abnormal return behavior, we also find evidence of insider trading before the announcement day.

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)0.000
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 score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.025
GPT teacher head0.214
Teacher spread0.189 · 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

Citations10
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Economics and FinanceSame topicCorporate Finance and GovernanceFrench-language works237,207