Information Transmission between China’s IH and SGX FTSE A50 Stock Index Futures Markets: The Role of Trading Restrictions
Bibliographic record
Abstract
After China’s stock market crash in 2015, the Chinese government imposed a series of trading restrictions on the stock index futures market. This paper examines how the relative informational role of China’s IH stock index futures and the SGX FTSE China A50 index futures varies when market trading mechanisms are subject to these major changes. We find that imposing the trading restrictions on IH futures substantially undermines their role in price discovery and volatility spillover, and renders them more susceptible to the fluctuations of A50 futures. Importantly, even after the trading restrictions are greatly eased at a later date, the importance of IH futures in price discovery and volatility spillover relative to that of A50 futures remains at a level much lower than before. Changes in liquidity and trading volumes imply that imposing the trading restrictions on IH futures drives investors to flee the IH futures market, but relaxing these restrictions is not able to attract investors back, making it difficult for IH futures to resume its important role in information transmission.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".