Transmission of Stock Return and Volatility Across G-7 Countries
Bibliographic record
Abstract
This paper investigates transmission of shocks in return and volatility across the G-7 countries using daily closing stock returns from 19th July 1994 to 30th January 2004. To capture observed asymmetry in volatility generated by the innovations within and across markets, a Vector Autoregressive-Exponential Generalized Autoregressive Conditional Heteroscedasticity (VAR-EGARCH) model has been used. Significant spillover in return and volatility are observed from US markets to other developed markets. There are evidences of strong regional dependency in volatility but not in return across the major European markets. Returns in Japanese market are significantly influenced by the US, UK and French markets, while all other markets (except Canada) exhibit significant return spillovers from Japanese market. Unlike returns, Japanese volatility is not at all influenced by any other G-7 markets. Volatilities in the European markets also contribute to the volatility in US and Canadian market. Own-volatility spillovers are generally higher than cross-volatility spillovers for all 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".