Institutional Investors and Crash Risk: Monitoring or Expropriation?
Bibliographic record
Abstract
This study tests two opposing views of institutional investors – monitoring versus expropriation – by investigating whether institutional ownership is positively or negatively related to future firm-specific stock price crash risk. We present robust evidence that institutional ownership is positively associated with future stock price crash risk. After further classifying institutional investors into transient, dedicated, and quasi-indexer types, we show that the overall positive relation between institutional ownership and future stock price crash risk is driven primarily by transient institutions, with dedicated institutions serving a monitoring role in reducing future stock price crash risk. We also find that institutional ownership by public pension funds (bank trusts, investment companies, and independent investment advisors) is significantly negatively (positively) associated with future crash risk. We also find that opaque financial reporting exacerbates the impact of institutional investors on future stock price crash risk. The findings in this study are shown inter alia to be robust to endogeneity concerns and alternative institutional investment metrics.
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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 | 0.014 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".