The Relation between Analysts' Forecasts of Long‐Term Earnings Growth and Stock Price Performance Following Equity Offerings*
Bibliographic record
Abstract
Abstract In this paper we evaluate the role of sell‐side analysts' long‐term earnings growth forecasts in the pricing of common equity offerings. We find that, in general, sell‐side analysts' long‐term growth forecasts are systematically overly optimistic around equity offerings and that analysts employed by the lead managers of the offerings make the most optimistic growth forecasts. In additional, we find a positive relation between the fees paid to the affiliated analysts' employers and the level of the affiliated analysts' growth forecasts. We also document that the post‐offering underperformance is most pronounced for firms with the highest growth forecasts made by affiliated analysts. Finally, we demonstrate that the post‐offering underperformance disappears once we control for the overoptimism in earnings growth expectations. Thus, the evidence presented in this paper is consistent with the “equity issue puzzle” arising from overly optimistic earnings growth expectations held at the time of the offerings.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.024 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".