Thirty Years of Canadian Evidence on Stock Splits, Reverse Stock Splits, and Stock Dividends
Bibliographic record
Abstract
AbstractThirty years of Canadian evidence has been used to shed light on the motivation and implications of stock splits, stock dividends, and reverse splits. The maximum 5-year period before and after the “event” month was focused and the changes in stock return, earnings per share (EPS), beta, trading volume, number of transactions, price to earning ratio (P/E), valuation, and corporate governance characteristics were examined. Strong information signaling effect of stock splits was found, as well as persistent superior performance and a favorable change in relative valuation are observed in the post-stock split period. The total trading volume increases after stock split ex-date while the trading volume per transaction decreases considerably, signifying a possible change in investor composition. However, no accompanying change was found in the governance environment. The overall evidence supports the signaling hypothesis as well as the optimum price and the relative valuation hypotheses. Stock dividend and reverse stock split firms have significantly weaker stock performance and operating performance than stock split firms. The negative trend does not improve in a long-term after the ex-date.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.011 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".