Seasonality in equities traded on the Toronto Stock Exchange between 1980 and 2019.
Bibliographic record
Abstract
This study investigates the day-of-the-week and month-of-the-year effects for equities traded on the Toronto Stock Exchange (TSX) between January 1, 1980, and December 31, 2019. As a conduit for the average price of stocks traded on the exchange, the S&P/TSX Composite Index (INDEXTSI: OSPTX) is used. The findings show that for the day-of-the-week effect, Mondays have underperformed while Fridays have overperformed. It is found that the day-of-the-week effect is present on the Toronto Stock Exchange at the 95th confidence level. Conversely, month-of-the-year effects are inconclusive; only one of three tests support the existence of the anomaly. Historical analysis shows that a $100.00 investment in the S&P/TSX Composite Index would have grown to $888.69 from January 1, 1980, to December 31, 2019, in a simple buy-and-hold strategy. However, if an investor had adopted this paper’s findings, they would have turned that same $100.00 investment into $3,444.49.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".