Chinese and Indian Stock Markets: Linkages and Interdependencies
Bibliographic record
Abstract
This paper examines the stock market linkages and interdependencies between China and India. We use the quantile regression approach as an alternative to Ordinary Least Squares estimation due to its flexibleness and robustness. Our results of the entire time period reveal the influence of Chinese CPI and ER on Nifty returns is not the same across the different quantiles. However, Chinese IR has no impact on Nifty returns. Further, Indian CPI has a negligible effect on SSE returns. In contrast, IR and ER do not affect SSE returns. This study also observes that the dependence structure between CPI and SSE returns indicates a negligible change post-recession period. However, the dependence structure between IR, ER, and SSE returns has not changed after the recession. Further, a significantly small change is found in the dependence structure between Chinese macroeconomic variables and Nifty returns post-recession.
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How this classification was reachedexpand
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 | 0.003 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".