Contagion Risks in Emerging Stock Markets: New Evidence from Asia and Latin America
Bibliographic record
Abstract
The purpose of this study is to investigate whether contagion actually occurred during three well-known financial crises in 1990s and 2000s: Mexican “Tequila” crisis in 1994, Asian “flu” crisis in 1997 and US subprime crisis in 2007. We apply dynamic conditional correlation models (DCC-GARCH(1,1)) to daily stock-index returns of eight Asian stock markets, six Latin American stock markets and US stock market. Defining contagion as a significant increase of dynamic conditional correlations, we test for contagion by using a difference test for DCC means. The results obtained shows that there is a pure contagion from crisis-originating markets to other emerging stock markets during these three crisis. However, the contagion effects are different from one crisis to the other. Firstly, during the Mexican crisis, contagion is detected in only the Latin American region. Secondly, during the Asian crisis, we find evidence of contagion in some markets in both the Asian and Latin American regions. Finally, contagion is proved to be present in all stock markets with the only exception for Brazil during US subprime crisis.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".