Interrelationships Between the Brazilian Financial Market and Foreign Financial Markets: New Evidence During and After the Subprime Crisis
Bibliographic record
Abstract
This study analyzed the financial interrelations between Brazil and selected foreign economies (United States (US), Germany, United Kingdom (UK), Japan and China) during and after the Subprime crisis, using three financial market indicators: stock market index, exchange rate and interest rate. The Vector Autoregressive approach and the Granger causality test were used, with daily data. The periods considered were: i) period of crisis (03/14/2007 to 03/31/2010); and ii) post-crisis period (04/01/2010 to 12/30/2019). The results revealed that in the Subprime crisis, the interrelations were intense, especially in the stock and exchange markets. IBOVESPA and Brazilian exchange rate were predominantly affected by the US, German and UK equity markets. Evidence in the post-crisis period showed considerably lesser interrelationships between the Brazilian financial market and foreign financial markets. Thus, the results confirmed that the crisis significantly intensified interrelations, with the main contagion channels as the stock markets and the foreign exchange 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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".