Dividend Policy, Economic Value Added, Market β, Firm Size and Stock Return
Bibliographic record
Abstract
This study aims to analyze the Effect of Dividend Policy, Economic Value Added (EVA), Market β and Firm Size on Stock Return and the existence of Firm Size in moderating these effects of blue-chip stock category listed in Indonesia Stock Exchange (IDX) during 2015 up to 2019 period. This study is a confirmatory research involving secondary data collected from annual report available at IDX website. The sample used is purposive sampling and research object is Dividend Policy, EVA, Market β and Firm Size as independent variables and Stock Return as dependent variable, and Firm Size as moderates variable. The analysis is performed using E-views 11.0 version. The result shows that Dividend Policy has significant negative effects while EVA and Market β has no effect on Stock Return. In addition, Firm Size moderates the relation between Dividend Policy and Stock Return, while having no moderating effect to the relation between EVA, Market β and Stock Return. The findings of this research imply that, for high stock performance like blue-chip stock, Dividend Policy affects the Stock Return and Firm Size moderates this effect.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".