Segmentation of the Chinese stock market: A review
Bibliographic record
Abstract
Abstract The Chinese stock market has a threefold segmented structure. Firstly, there is a division between floatable and nonfloatable shares, known as the split‐share structure. Before 2005, more than two‐thirds of the shares outstanding were nonfloatable. This structure limited shareholders’ ability to exercise governance rights through stock trading. While largely dismantled by the 2005 reform, the split‐share structure has not been fully eliminated. Secondly, floatable shares can be issued in multiple currencies. However, shares denominated in the domestic currency often trade at a premium over those denominated in foreign currencies. This premium can be explained by the differences in target investors and the trading restrictions. Thirdly, stocks denominated in the domestic currency are sorted into different market tiers depending on the firms’ profitability and market capitalization. The limited mobility of stocks across different tiers engenders tier‐specific characteristics, such as high family ownership and venture‐capital backing, which have not been sufficiently studied. In this paper, we delineate the three aspects of market segmentation, offer critical comments on the caveats of the extant studies, and propose topics for future research.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".