Impacts of COVID-19 on the Return of Sustainable Stocks of Thailand
Bibliographic record
Abstract
Objective: This study aimed to investigate the impact of Covid-19 pandemic and vaccination on the sustainable stock price in the Stock Exchange of Thailand (SET) which be controlled by economic factors (as consumer price index and exchange rate) Method: This paper employs Panel Autoregressive Distribution Lag model. These panel data were collected from the 93 sustainable stocks in SET during January 2017 to September 2022. Results: The empirical results reveal that the COVID-19 pandemic caused the decline of the stock price, while the vaccination caused of the price increasing. In addition, the exchange rate depreciation also pushed the stock price and consumer price index (CPI) increasing pull the price down. Conclusion: The results of this study revealed the influences of a terrible incident as an obstacle for the economic sector at the global level, i.e., the COVID-19 pandemic and its solutions/vaccines, and the influences of economic factors affecting the prices in the sustainable stock group. Therefore, the use of measures to promote vaccination would reflect the investors’ confidence in sustainable stocks.
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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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".