Do Analysts Practice What They Preach and Should Investors Listen? Effects of Recent Regulations
Bibliographic record
Abstract
ABSTRACT: From 1994 to 1998, Bradshaw (2004) finds that analysts' stock recommendations relate negatively to residual income valuation estimates (scaled by current price) but positively to valuation heuristics based on the price-to-earnings-to-growth ratio and long-term growth. These results are surprising, especially considering that future returns relate positively to residual income valuation estimates and negatively to heuristics. Using a large sample of analysts for the 1993–2005 period, we consider whether recent regulatory reforms affect this apparent inconsistent analyst behavior. Consistent with the intent of these reforms, we find that the negative relation between analysts' stock recommendations and residual income valuations is diminishing following regulations. We also show that residual income valuations, developed using analysts' earnings forecasts, relate more positively with future returns. However, we document that stock recommendations continue to relate negatively with future returns. We conclude that recent regulations have affected analysts' outputs—forecasted earnings and stock recommendations—but investors should be aware that factors other than identifying mispriced stocks continue to influence how analysts recommend stocks.
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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 | 0.014 | 0.149 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".