Relations between Volatility and Returns of Exchange Traded Funds of Emerging Markets and of USA
Bibliographic record
Abstract
This paper investigates linkages between equity returns and transmission and persistence of volatilities between US and selected key emerging countries during 2012. The data set consists of daily returns of exchange traded funds (ETF) of Brazil, India, Indonesia, Mexico, Russia, S. Korea, Turkey and US. The results of the analysis indicate the existence of significant co-movement of returns among all ETFs, as well as transmission and persistence of volatilities of most emerging markets, with the exception of Turkey and Russia, where the volatilities were unaffected by volatilities of other markets. Turkey¡¯s volatility was only transmitted to Indonesia. The findings also indicate that the US market volatility was only transmitted to Indonesia and not to any other market, and the only market whose volatility was transmitted to the US was that of Mexico. The presence of spillovers among stock markets¡¯ return series and persistence of volatilities is indicative of efficiency (or inefficiency) in stock markets, and therefore, is useful to investors interested in diversifying their portfolios.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.001 | 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 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".