Can The Easing Of COVID-19 Restrictions Enhance the Performance of Sectors in The Stock Market?
Bibliographic record
Abstract
COVID-19 pandemic has affected stock prices in many sectors of financial markets and this can be seen in many countries all over the world. The main enquiries in this study included whether the negative effect of COVID-19 pandemic was converted into a positive reaction in the financial markets after the restriction related to the pandemic were gradually relaxed and which sectors were more affected by this relaxation. These inquiries were investigated through examining the case of the state of Qatar because it has an attractive investment environment as the richest country in the Arab world. Quantitative method was followed to answer the enquiries of this study by testing the performance of the stock indices in the sectors of Qatari market for the period from 25 April, 2021 to 18 November, 2021. The performance of the index of each sector was measured using risk-adjusted performance measures. Data of the study were analyzed using Friedman test. Study results revealed that the gradual lifting of the restrictions has positively affected the performance of the sectors in the stock market and that the magnitude and direction of the effect was different on each 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 | 0.002 | 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 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".