Information Acquisition Costs and Analysts’ Cash Flow Forecasts: The Role of Management Cash Flow Forecasts
Bibliographic record
Abstract
We examine whether the provision of managerial cash flow forecasts is a significant predictor of analysts’ decision to cover a firm with cash flow forecasts. Unlike managerial earnings forecasts, which are often issued to walk down analyst earnings estimates, managers issue cash flow forecasts to counter bad earnings news and lessen the cost of investor and analyst information acquisition (Wasley & Wu, 2006). Motivated by the increasing popularity of managerial cash flow forecasts and prior empirical evidence that analysts are less likely to follow a firm for which the costs of acquiring financial information are prohibitive (e.g., Liu, 2011), we predict and find that the provision of managerial cash flow forecasts is a significant determinant of the likelihood of analyst cash flow coverage. We also find that analysts are less likely to issue cash flow forecasts when the effort necessary to follow a firm is high. Together, the evidence suggests that the existence of management cash flow forecasts is an important determinant of analysts’ cash flow coverage.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| 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".