Does Corporate Governance Quality Influence Insider Trading around Private Meetings between Managers and Investors?
Why this work is in the frame
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Bibliographic record
Abstract
SYNOPSIS We examine the effectiveness of corporate governance in influencing insider trading around private in-house meetings (hereafter “private meetings”) between management and investors in China. Consistent with better corporate governance curbing (1) disclosure of nonpublic price-sensitive information and (2) insider trading, we find that better governance quality is associated with reduced insider trading frequency, value, and profitability around private meetings. Firms with better corporate governance appear to exchange less price-sensitive information with outsider investors around private meetings, which limits the opportunity to make profitable insider trades. Our results are economically significant and robust using instrumental variable and propensity score matching approaches to address endogeneity. We argue that improving corporate governance quality may be a partial substitute for costly government regulation designed to curb insider trading around private meetings. JEL Classifications: G34; G14; G18.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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