Common stock return and international listing announcements: Condititional tests of the mid segmentation hypothesis
Bibliographic record
Abstract
Recent theoretical work on mild segmentation suggests that tests of dual listing should be conducted as joint tests: a) a test of changes in market integration that may affect asset returns through investors portfolio reallocations as the choice set changes, and b) a test of changing risk premium/information effects. Previous empirical studies on common stocks have been unable to identify significant positive abnormal returns associated with international listing. However, such studies have not formally tested for changes in market integration through time. In addition, they have not examined announcement dates, which should be the focal point in testing for valuation effects. Unlike previous studies, our analysis concentrates on both the period surrounding the earliest public announcements by Canadian companies of their intentions to seek a U.S. listing for their common shares on the NYSE, AMEX, or NASDAQ as well as the date of U.S. listing during the period 1985-96. This period encompasses significant changes in the regulatory environment which might be perceived to enhance the integration of the two markets. Relying on a conditional asset pricing model subject to time-varying volatility, the results of this study fail to support the view that market integration has increased between the Canadian and U.S. stock markets over the 1985-96 period. The significantly positive announcement effects of Canadian stock listings in the U.S.
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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 | 0.005 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".