The Post‐earnings Announcement Drift: A Pre‐earnings Announcement Effect? A Multi‐period Analysis
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
For many years, the post‐earnings announcement drift (PEAD) has been accepted as an anomaly to the efficient markets hypothesis. This drift subsequent to earnings announcements has been ascribed to the incomplete incorporation by the market of the information in these earnings announcements. Interestingly, over the past five decades of extensive research, no rational economic explanation of the PEAD has been found. In addition, there has been no specific consideration of the effect of new economic information subsequent to the earnings announcements. Our multi‐year examination of the cumulative abnormal return (CAR) incorporates the effect of economic information subsequent to the earnings announcement of traditional PEAD studies. Our analysis shows that a drift of CAR versus time can arise without recourse to invoking market inefficiency. Our results are consistent for three samples covering the period 1974–2016. We do not assert that we prove that there is no component of the traditional PEAD due to market inefficiency. Rather, our results show that studies to determine whether there is a market inefficiency component of the PEAD should use a multi‐period approach in order to account for the effect of economic information subsequent to the earnings announcements and thereby focus more precisely upon the cause of the PEAD reported in previous research studies.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it