The response of Canadian stocks to the COVID-19 pandemic: the case of a developed economy
Bibliographic record
Abstract
The full extent of the COVID-19 pandemic is still unfolding and has evolved from a public health crisis to a major economic crisis. Its impact is felt by most businesses and capital markets worldwide. Canada is one of the G7 economies that felt the enormous economic and social impact of the pandemic. In this study, an ordinary least square (OLS) model is used to assess the impact of the COVID-19 pandemic on the Toronto Stock Exchange during 2020 and 2021. Growth in the confirmed COVID cases, ICU admissions, and government restrictions negatively impacted the Toronto Stock market returns; however, growth in hospitalisations positively impacted them. The sub-sectors of consumer discretionary, industrial, and financial services ranked in the top three positions respectively on the basis of risk-adjusted returns, while healthcare was positioned at the bottom of all ten sub-sectors. Furthermore, small caps outperformed the large caps and TSX composite index.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".