Risk arbitrage trading and the characteristics of arbitrage spreads : the Canadian evidence
Bibliographic record
Abstract
Using a sample of Canadian mergers data from Securities Data Corporation (SDC) for the 1990-1997 period, and returns data from the TSE Western database, I demonstrate that the average arbitrage spreads of Canadian mergers are significantly higher than those of their American counterparts. The arbitrage spread is defined as the percentage difference between the bid price and market price one day after the initial announcement. I also demonstrate that the cross-sectional variation of these spreads is high, and negative in some instances. Buying the targets of the entire sample and shorting their bidders does not yield abnormal returns. However, smarter trading focused on specific segments of the sample yield short-term abnormal returns. I find that trading strategies based on buying the following three categories of targets offer the highest level of abnormal return. The categories are; target firms in the largest quartile of the relative size ratio; firms subject to both cash offers and firms subject to cash tender offers. Typical of merger studies, we find that target companies experience highly significant abnormal returns on the announcement day, and slightly lower significant abnormal returns on the following day.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".