The Impact of COVID-19 on the Malaysia Stock Market: Finance Sector
Bibliographic record
Abstract
Novel coronavirus outbreak since December 2019 has infected more than 1 million people to this day. The severe impact of the coronavirus has affected the world economy including Malaysia. Some countries have implemented lockdowns to contain the virus from spreading and this affected business heavily especially financial market. The dependent variables used in this research is the Kuala Lumpur Financial Index. The independent variables are the number of COVID-19 daily cases, the number of COVID-19 death, the volatility index and the Brent Crude Oil Price. The pandemic has affected the whole economy as the Brent crude oil has plummet below USD40 per barrel. Therefore, this paper will include Brent Crude oil price as the variable to identify the relationship between the stock market index. Investors’ concern on the COVID-19 cases and death has impact on the market. This paper will focus on the impact of COVID-19 virus on the finance sector in Malaysia. This sector mobilizes savings and allocated credit; thus, it has significant contribution in raising people’s standard of living. The sample period used in this study is from 1st January to 31st July 2020.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".