Stock Market Relationship in South Asia: An Empirical Analysis
Bibliographic record
Abstract
Literature indicates that there are several studies that have focused on stock market relationships and integration but very limited studies are found in this area that have focused for South Asian markets. Few that have studied stock market relationships and market integration in this region have never included Bhutan, probably due to unavailability of data on Bhutanese stock market or because it is too insignificant in terms of regional market. Particularly the relationship between Bhutanese stock market and Indian stock market is expected to be positive and significant given the very close economic ties/dependence with India. Correlation and regression analysis (data sample includes January 2006 to December 2011 for weekly returns) do not show relations between Bhutanese, Indian or any other stock returns except between Indian and Pakistani market returns. Few time varying effects were noticed when correlations were calculated for different set of split data. In general South Asian markets seem quite independent of each other. Indian stock market, which is more proficient in the region, was expected to have some influence but the results do no support this. Based on the Granger causality test, Indian market seems to provide unidirectional effect on most of the neighbouring stock markets.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".