Dynamic multibeta macroeconomic asset pricing model at NAFTA stock markets
Bibliographic record
Abstract
Recent financial literature confirms the influence of macroeconomic factors in asset pricing for the case of developed countries. Additionally, an ample body of literature also suggests a trend towards integration among them. Because the same kernel of macroeconomic factors affects their returns. The evidence for emerging markets is inconclusive. Particularly, emerging markets have been identified as partially segmented from global markets. Studies at regional level confirm this view. Applying a multifactor beta model, this papers examines the case of the HAFTA countries, Mexico, Canada and United States. Its objectives are, first, identify the relationship between local macroeconomic factors and asset pricing at each market; and, second, examine the integration of each market to global market macroeconomic variables. Results show that local factors weight more than international factors at each market, revealing mild segmentation among these markets. The level of integration of local markets with global variables is greater for United States, while for Mexico is the lowest.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".