Financial Market Integration Between Stock Market From North American Free Trade Agreement (NAFTA) Member
Bibliographic record
Abstract
Economic recession or crisis could show a higher possibility of financial crisis transmission in an integrated stock market. Integration between financial markets is a channel of spreading the devastating effects of the crisis. The objective of this study is to detect significant interactions among the stock markets of countries that are members of the North American Free Trade Agreement (NAFTA). NAFTA is a regional partnership with members from the United States, Canada and Mexico that are committed to reducing trade and investment barriers between member countries. The methodology of this research with VAR VECM model consists of three stages, the first analysis of the presence impact of the stock market index using the Granger Causality Test. Second, analyze the speed of response of an index to a change / shock in another index using the Impulse Response Function (IRF). The third stage analyzes the impact of changes / shocks from one index to other indices by using Variance Decomposition. From the 5 sets of stock market data for NAFTA countries, the results of the study show that there is only one cointegration. When viewed in the cointegration process of each of the two data series, cointegration occurs between the Nasdaq index with TSE and Nasdaq with MSE. Whereas TSE and MSE did not find any cointegration.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.005 | 0.001 |
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".