Bibliographic record
Abstract
This paper provides new insight into how information is disseminated when markets are subject to short sales restrictions by examining the relationship between short interest and returns for Canadian stocks. Short interest is defined in relation to trading volume because volume reflects information in the market. The results strongly support the assertion that short sales reflect bad news in Canada. The paper further finds that short sales convey more negative information for small firms because the supply of shortable shares is more constrained for these firms. In addition, short sales are less informative for stocks with associated options because the option market enhances the informational efficiency of the stock market. Importantly, the evidence suggests that informed traders short sell interlisted stocks in Canada, rather than the U.S., to exploit lower execution costs. Thus, short sales in Canada are more informative than in the U.S.. Together the results suggest that less restrictive regulation of short sales will improve the informational efficiency of markets. Selling borrowed stock is a direct method to take advantage of declines in stock prices resulting from adverse information. This paper provides new insight into how information is disseminated when
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 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) | 0.264 | 0.034 |
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".