Is guidance a macro factor? The nature and information content of aggregate earnings guidance. Working paper
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
Although there is a great deal of research that documents the information content of management earnings forecasts at the firm level, there is almost no research on the informativeness of aggregate guidance. We argue that aggregate earnings guidance is informative at the market/economy level through its effects on expectations about market-level expected future cash flows and expected returns. Consistent with aggregate guidance capturing information about economy-wide cash flows, we find that aggregate guidance, especially relative levels of quarterly downward guidance, is associated with analyst- and time-series-based measures of aggregate earnings news. We also find that guidance affects market returns in those months each quarter when the most guidance is released, and that relative levels of downward guidance are especially informative. Overall, the evidence supports our contention that guidance affects market returns by aggregating news about market-level cash flow shocks and through its effects on market uncertainty.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| 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 it