Trading-services sector: Quarter report announcement effect towards the stock price in Malaysia / Nor Atiyah Ismail
Bibliographic record
Abstract
This research aim to study on how quarter report announcement effect towards the stock price in trading-services sector of public listed company in Malaysia and to identify which variables has the most effect of the stock price movements in this sector. Data were collected quarterly started from 1st quarter of 2012 until 4th quarter 2017 for 10 trading services companies listed in Malaysia. The internal factors such as the firm's revenue, earning per share, net profit, dividend and net tangible asset that updated quarterly in financial report are used as the independent variables for the research. These five independent variables that used in this study to examine the relationship of firm quarter performance toward stock price. The methods that were used are statistical analysis like Normality Test, Correlation Analysis, Descriptive Analysis, Heteroscedasticity Test and Panel Ordinary Least Square Analysis are use to measure the level of significance in order to know which factor have stronger effect towards firm's stock price. The findings conclude all variables are expected to be positive relationship with the stock price of the trading-services sector.
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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 | 0.003 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".