When Is the Client King? Evidence from Affiliated‐Analyst Recommendations in China's Split‐Share Reform
Bibliographic record
Abstract
ABSTRACT China's split‐share reform of 2005 (the Reform) converts the previously restricted shares held by founding shareholders to shares tradable on the open market. Against this backdrop, we study how underwriter‐affiliated analysts and firms' large shareholders interact in the event of the latter's sales of restricted shares. We document that recommendations made by affiliated analysts are significantly more optimistic when firms' large shareholders plan to sell their restricted shares. This optimism, however, is associated with negative post‐sale stock returns, suggesting large shareholders profit from share sales. Furthermore, large shareholders sell more restricted shares through the affiliated brokerages for which analysts have issued more optimistic recommendations and firms under their control are more likely to appoint such brokerages as lead underwriters when they refinance in the future. The affiliated analysts also conduct more site visits to the firms after the share sales, thereby improving their earnings‐forecast accuracy. Our analysis shows how conflicts of interest by financial intermediaries arise following the Reform and lead to large shareholders' extraction of rents from public investors.
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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 | 0.005 | 0.029 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".