Options trading prior to takeover rumors
Bibliographic record
Abstract
Purpose In this paper, the authors examine options trading in firms that soon become rumored takeover targets. This study also examines whether measures of informed trading can predict target returns (upon rumor announcement and over the post-rumor period) and/or predict which rumors lead to bids. The authors further assess whether the informed trading they observe is more prevalent in the options market or the equity market. Design/methodology/approach This study calculates abnormal options volume using a market-model approach that accounts for different attributes of options trading. The authors construct a control sample and compare equity options trading of firms in their sample with that of the control sample. In addition, the authors fit a series of regressions to examine whether pre-rumor abnormal options trading can predict rumor accuracy in a multivariate setting. Findings The authors find that the volume of options traded is abnormally high over the pre-rumor period while the direction of option trades (abnormal call volume minus abnormal put volume) prior to takeover rumors predicts forthcoming takeover announcements, rumor date target firm returns and post-rumor target firm returns. The results are robust when controlling for publicly available information, when using a control sample, and when using alternative measures of informed trading. Originality/value This study is the first to provide evidence of informed options trading prior to a broad sample of takeover rumors. In addition, this study contributes to the literature on takeover predictability and profitability by showing that various pre-rumor measures of informed options trading significantly predict bid announcements. The authors also contributes to the literature on price discovery by providing evidence that informed investors are more likely to trade in the options market than in the equity market during the pre-event period.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".