Price Shocks, News Disclosures, and Asymmetric Drifts
Bibliographic record
Abstract
ABSTRACT Motivated by investor disagreement and corporate disclosure literatures, we examine how stock price shocks affect future stock returns. We find that both large short-term price drops and hikes are followed by negative abnormal returns over the subsequent year, consistent with the conjecture that price shocks are useful indicators of intertemporal spikes in investor disagreement and investor opinion converges gradually. The asymmetric drifts involve return continuation for negative price shocks versus return reversal for positive price shocks, and are in sharp contrast to the general findings of symmetric drifts in corporate event studies. Moreover, price shocks associated with public news events are followed by significantly weaker downward drifts, suggesting that news disclosures mitigate disagreement-induced overpricing. Examining the dynamics of a disagreement proxy during and after price shocks, we provide further evidence for the disagreement hypothesis. The economic significance of the price shock effect is illustrated with a revised momentum strategy that generates an annualized abnormal return of 16.92 percent.
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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 | 0.002 | 0.001 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".