Do Institutional Investors Prefer Near‐Term Earnings over Long‐Run Value?*
Bibliographic record
Abstract
Abstract This paper examines whether institutional investors exhibit preferences for near‐term earnings over long‐run value and whether such preferences have implications for firms' stock prices. First, I find that the level of ownership by institutions with short investment horizons (e.g., “transient” institutions) and by institutions held to stringent fiduciary standards (e.g., banks) is positively (negatively) associated with the amount of firm value in expected nearterm (long‐term) earnings. This evidence raises the question of whether such institutions myopically price firms, overweighting short‐term earnings potential and underweighting long‐term earnings potential. Evidence of such myopic pricing would establish a link through which institutional investors could pressure managers into a short‐term focus. The results provide no evidence that high levels of ownership by banks translate into myopic mispricing. However, high levels of transient ownership are associated with an over‐ (under‐) weighting of near‐term (long‐term) expected earnings, and a trading strategy based on this finding generates significant abnormal returns. This finding supports the concerns that many corporate managers have about the adverse effects of an ownership base dominated by short‐term‐focused institutional investors.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".