Institutional Investors’ Trading Behavior in Mergers and Acquisitions
Bibliographic record
Abstract
Abstract We investigate institutional investors’ trading behavior of acquiring firm stocks surrounding merger activities for the period 1992–2001. We label investment companies and independent investment advisors as active institutions and banks, nonbank trusts, and insurance companies as passive institutions. We analyze the trading behavior of active and passive institutions surrounding merger announcements and their eventual resolution. Our results indicate that active institutions significantly increase their holdings of acquiring firm stocks for mergers with higher announcement period abnormal return and this increase is more pronounced for stock mergers than cash mergers. Active institutions display preference for stock proposals at the merger announcement on the basis of their prior beliefs and this is explained by the “overreaction phenomenon.” However, they update their beliefs between announcement and final resolution as more information arrives into the market. Finally, active institutions appear to correct their overreaction behavior by displaying their greater preference for cash proposals as compared to stock proposals at the quarter of eventual outcome. The trading behavior of passive institutions suggests that these institutions disregard the market response of merger announcement in trading acquiring firm stocks at the announcement quarter. The passive institutions gradually update their beliefs and utilize the information released at the announcement in rebalancing their portfolios at the final resolution.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".