How Retail vs. Institutional Investor Sentiment Differ in Affecting Chinese Stock Returns?
Bibliographic record
Abstract
This paper evaluates the impact of retail investors’ bullish sentiment in comparison to that of financial institutions on the return of Chinese CSI 300 index stocks over the period of 2015 to 2023. We document several regularities. First, the stronger the retail (institutional) investors’ bullish sentiment, the lower (higher) the stock returns, and such contrasting associations hold after an array of robustness tests. Second, mechanism test results show that the retail and institutional investor sentiments affect stock returns mainly by influencing the analysts’ attention and the equity liquidity. Third, heterogeneity analyses reveal that the adverse effect of retail investors’ bullish sentiment on stock returns becomes more prominent for non-state-owned, manufacturing, and non-heavily polluted enterprises, but the positive effect of the emotions expressed by institutional investors on stock returns is greater for non-state-owned, non-manufacturing, and heavily polluted enterprises. Therefore, this paper sheds light on detailing of investor sentiment types and hedging investment risks.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".