Biotechnology Stock Prices before Public Announcements: Evidence of Insider Trading?
Bibliographic record
Abstract
Background Unique financial challenges faced by biotechnology companies developing therapeutics have contributed to the creation of a highly sensitive market, where stock prices are capable of great fluctuation. The potential for significant financial reward and the nature of the scientific review process make this industry susceptible to illegal share trading on nonpublic information. We examined stock prices of biotechnology products before and after announcement of Phase III clinical trial and Food and Drug Administration (FDA) Advisory Panel results for indirect evidence of insider trading. Methods Biotechnology stock prices were recorded for 98 products undergoing Phase III clinical trials and 49 products undergoing FDA Advisory Panel review between 1990 and 1998. Prices were recorded for 120 consecutive trading days before and after public announcement of these two events. We compared the average change in stock price of successful products ('winners') with unsuccessful products ('losers') before the public announcement of results for both critical events. Results The difference between average stock price change from 120 to 3 days before public announcement of results of Phase III clinical trial winners (+27%) and losers (–4%) was highly significant (P=0.0007). A similar but non-significant difference was observed between the average stock price of winning (+27%) and losing products (+13%) before FDA Advisory Panel review announcements (P=0.25). Conclusions Our results provide indirect evidence that insider trading may be common in the biotechnology industry. Clinical investigators may wish to consider this issue before participating in any equity position in the biotechnology industry, especially if they are going to perform research for those companies.
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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 | 0.010 | 0.059 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".