The Impact of Intraday Timing of Earnings Announcements on the Bid-Ask Spread and Depth
Bibliographic record
Abstract
Libby, Mathieu, and Robb (2002) investigate, among other things, the impact of intraday timing of earnings announcements on the bid-ask spread and depth for a sample of firms listed on the Toronto Stock Exchange. They document, in a univariate setting, that the spread is relatively wider and the depth lower after announcements declared during nontrading hours than after announcements released during trading hours. This study extends their research by (1) investigating earnings announcements declared by firms traded on the NYSE or AMEX, (2) addressing this issue in a multivariate setting, (3) exploring before-open and after-close announcements separately, and (4) analyzing the impact by half-hour interval. Interestingly, my results indicate, opposite to the findings by Libby, Mathieu, and Robb (2002), that the spread is relatively smaller and the depth higher after overnight announcements than after daytime announcements. These findings are robust to firm-specific factors, cross-listings, differences in the content of daytime and overnight releases, and intraday timing consistency. In addition, this effect occurs after before-open and after after-close announcements, and the analysis by half-hour interval reveals that the impact on the spread (depth) lasts for four (seven) trading half hours.
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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".