Market Reactions to Changes in the S&P/TSX SmallCap Index
Bibliographic record
Abstract
Earlier studies find inconsistent results about market reactions to changes in large cap and small cap stock indexes. This study extends the literature by examining stock price and trading volume reactions to changes in the Canadian S&P/TSX SmallCap index, and offers several conclusions. First, consistent with previous studies, we find that the way a stock is added to or removed from the index makes a large difference. Specifically, pure additions to the S&P/TSX SmallCap index show significant positive cumulative abnormal returns in the period before and on the announcement day. In contrast, downward additions experience a significant negative abnormal return on the effective day. Similarly, pure deletions show significant negative cumulative abnormal returns before the announcement day, as well as on both the announcement and effective days. On the other hand, upward deletions do not experience significant abnormal returns during the event period.Second, we find a permanent stock price increase for pure additions to the S&P/TSX SmallCap index. Pure additions also tend to experience an increase in trading volume and decline in the relative bid-ask spread. In contrast, pure deletions show a permanent price decline that is partially reversed immediately after the effective day.Third, the significant abnormal trading volume on the effective day considerably exceeds the significant abnormal trading volume on the announcement day for all groups. This could be explained by the trading behavior of index funds that buy additions and sell deletions on the effective day near closing price to minimize tracking error.
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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 | 0.008 |
| 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 | 0.001 | 0.001 |
| 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".