Discretionary Disclosures to Risk‐Averse Traders: A Research Note
Bibliographic record
Abstract
Abstract Verrecchia (1983) investigates a manager's incentives for costly, discretionary disclosure of his information to risk‐averse traders when the functional form of prices is exogenously specified. We extend Verrecchia (1983) by deriving the endogenously determined functional form of prices that would arise when all traders have constant risk tolerance. We show that these endogenously determined prices are inconsistent with the assumed prices in Verrecchia (1983) when the manager elects to not disclose. We derive the manager's disclosure strategy for our setting and extend the comparative static results in Verrecchia (1990) for risk‐neutral traders to a setting where traders have constant risk tolerance and prices are endogenously derived. Further, in our setting, discretionary disclosure does not affect how traders price risk of different outcomes. Also, we offer a representation of risk‐averse traders' prices using risk‐adjusted distributions. Finally, these results provide implications for empirical‐archival discretionary disclosure studies.
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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 | 0.006 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".