The association between quarter length, forecast errors, and firms’ voluntary disclosures
Bibliographic record
Abstract
Abstract Approximately 60 percent of adjacent fiscal quarters contain a different number of calendar days. In preliminary analyses, we find the change in quarter length is significantly associated with the changes in sales and earnings and that analysts condition on the prior quarter's results when making their forecasts. These results indicate that it is important for analysts to adjust for changes in quarter length when making forecasts. However, we find the quarterly change in days is positively associated with analysts’ sales and earnings forecasts errors, where forecast error equals the actual earnings minus the forecasted earnings. These results indicate that analysts systematically underestimate (overestimate) performance when quarter length increases (decreases). We find evidence indicating investors make similar errors as returns around earnings announcements are positively associated with the change in quarter length, but only when changes in firm performance is more sensitive to changes in quarter length. Corroborating these findings, managers are more (less) likely to discuss quarter length during conference calls when quarter length decreases (increases). These results are consistent with managers’ strategic disclosure incentives. In summary, our evidence suggests analysts and investors fail to fully take account of the quasi‐mechanical effect that quarter length has on firm performance and managers strategically alter their voluntary disclosures to take advantage of these failures.
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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 | 0.001 | 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 | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".