Public Predisclosure Information, Firm Size, Analyst Following, and Market Reactions to Earnings Announcements
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract: This study examines the effects of public predisclosure information on market reactions to earnings announcements. We develop an empirical measure of public predisclosure information impounded in price prior to earnings announcements by cumulating abnormal returns on public news release dates during the quarter. Consistent with prior literature, we document a negative association between this measure and market reactions to subsequent earnings announcements. Moreover, we find that after controlling for this measure, firm size and analyst following are significantly positively associated with market reactions to earnings announcements. Contrary to prior empirical evidence, our results suggest that, after controlling for actual predisclosure information impounded in price, market reactions to earnings announcements are greater in magnitude for larger, more widely‐followed firms than for smaller, less widely‐followed firms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.013 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it