Trader Participation in Disclosure: Implications of Interactions with Management
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
ABSTRACT Technological advances are creating a shift in the information disclosure environment allowing more investors to interact with management. We examine three key levels of trader‐management interaction to assess the accuracy of traders' market‐tested value estimates and resulting market price. These data require an engaging experiment and a complex, contextually rich asset, which we create by playing a popular gaming app before the experiment. Participants view financial information, ask management questions, estimate value, and trade. We find that receiving non‐personalized question responses improves trader estimates of value and market price efficiency relative to when traders ask questions but do not expect a response. This occurs because traders exert more effort estimating value and trading. However, receiving personalized versus non‐personalized responses harms value estimates and market efficiency. This occurs because traders receiving personalized responses fixate on the interaction with management, dividing their attention and diverting it away from valuing and trading the asset.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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