Tail Risk Spillovers in Stock Markets Between G7 and BRICS: New Evidence from CAViaR and TVP-VAR Connectedness Approach
Bibliographic record
Abstract
This study examines the tail risk spillover effects of G7 and BRICS stock markets by employing the onditional Autoregressive Value-at-Risk (CAViaR) model and the time-varying parameter vector autoregression (TVP-VAR) connectedness approach and further discusses the impact of the federal funds rate rise and the Silicon Valley Bank’s bankruptcy. It concludes that the risk interconnectedness of the pairs US–Japan and US–India stock markets has risen the most since the Federal Reserve entered the interest rate hike cycle in 2022. After the bankruptcy of Silicon Valley Bank, we only observe an obviously stronger bilateral interconnectedness for the pair US–Canada stock markets. In addition, the G7 countries (excepting Japan) transmit more risk than those of the BRICS countries, and the changes of tail risk received by the BRICS are greater. These findings have crucial implications for policymakers, encouraging reasonable capital control to avoid excessive reactions of the domestic stock market to external shocks.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".