Financial Integration of the European, North America, Asiatic and Japanese stock markets from 2003 to present times
Bibliographic record
Abstract
We apply an integration/segmentation analysis between the European (EU) market and the North America stock market (US and Canada), the Asian Stock Market (AS) and the Japanese (JP) market. The analysis is carried out from 2003 until the present time. We apply the Jorion and Schwartz (1986) methodology and extend the work of Brooks et al. (2009) using a simpler Capital Asset Price Model (CAPM) and the Market return downloaded from the Fama French website for the time period analysed. Our results in this empirical study show integration between the European portfolios and the US stock market and the Asian Portfolios and the US stock market in the full time period analysed. Although the methods applied in this paper have been already introduced in the literature, this is the first time that they are applied systematically to compare the integration and segmentation between different economies and a given portfolio set. This systematic approach helps to establish the conclusiveness of their forecasts.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".