Concurrent Earnings Announcements and Analysts' Information Production
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 We examine whether financial analysts are subject to limited attention. We find that when analysts have another firm in their coverage portfolio announcing earnings on the same day as the sample firm (a “concurrent announcement”), they are less likely to issue timely earnings forecasts for the sample firm's subsequent quarter than analysts without a concurrent announcement. Among the analysts who issue timely earnings forecasts, the thoroughness of their work decreases as their number of concurrent announcements increases. In addition, analysts are more sluggish in providing stock recommendations and less likely to ask questions in earnings conference calls as their number of concurrent announcements increases. Moreover, when analysts face concurrent announcements, they tend to allocate their limited attention to firms that already have rich information environments, leaving behind firms in need of attention. Overall, our evidence suggests that even financial analysts, who serve as information specialists, are subject to limited attention. JEL Classifications: G10; G11; G17; G14. Data Availability: Data are publicly available from the sources identified in the paper.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.003 |
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