Bibliographic record
Abstract
ABSTRACT We study executive equity contributions to nonqualified deferred compensation plans, which consist of the election to defer part or all of the executive's annual base salary and other cash pay into the company's stock. These transactions provide executives with an alternative channel to purchase shares in the firm while benefiting from an affirmative defense against illegal insider‐trading allegations. Using a large sample of executive equity deferrals over 2000–2014, we find evidence that executives use these transactions as a means to acquire the company's stock during blackout windows. Consistent with the conjecture that deferrals can benefit from lower litigation costs that inhibit insider trades before the release of corporate news, we also find that the deferred amounts are significantly higher (lower) before the disclosure of good (bad) earnings news. These results suggest that executives can use equity deferrals to circumvent Rule 10b5 trading restrictions and generate significant returns through the timing and content of corporate disclosures around these transactions. Together, our evidence supports the recent concerns that executives might be engaging in strategic information releases around Rule 10b5 transactions.
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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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".