EPS‐motivated share repurchases and wealth transfer
Bibliographic record
Abstract
Abstract We study the association between earnings‐per‐share (EPS)‐motivated share repurchases and wealth transfer between the repurchasing firm's ongoing shareholders and selling/transacting shareholders. Compared to other repurchases, EPS‐accretive repurchases are associated with greater wealth transfer from ongoing to selling shareholders, thereby reducing shareholder value for ongoing shareholders. We also find that EPS‐accretive repurchases used to meet/beat analyst forecasts are associated with incrementally more wealth reduction for ongoing shareholders, compared to other EPS‐accretive repurchases. These findings suggest that, compared to other repurchases, repurchases driven by EPS concerns are more likely to benefit selling shareholders at the expense of ongoing shareholders (all else equal). Using quarterly earnings announcements, we find that investors price this one‐time repurchase‐induced wealth reduction for ongoing shareholders. Despite this, however, investors appear to take a positive overall view of EPS‐driven repurchases, suggesting that the benefits of such repurchases for ongoing shareholders outweigh the one‐time wealth reduction from such repurchases. Consistent with this, we find that EPS‐motivated repurchases are associated with better future operating performance.
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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 | 0.022 |
| 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) | 0.004 | 0.001 |
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".