In Search of International Integration: An Examination of Intraday North American Trading of Canadian Dually Listed Stocks
Bibliographic record
Abstract
We examine international equity market integration using intraday data for a sample of Canadian stocks that trade on both the Toronto Stock Exchange (TSE) and the New York Stock Exchange (NYSE). There are several advantages of this sample: Canadian stocks trade as stocks (not ADRs) in the U.S.; investors in each country are free to route trades to the foreign market; the additional cost of trading abroad is small, especially for institutional traders; and the markets have perfectly synchronous trading hours. These conditions allow us to examine both whether the law of one price holds and the process by which deviations from it are corrected. Our tests show the U.S. dollar prices of the stocks in the two markets to be cointegrated. The estimated error correction models show rapid adjustments to deviations from the law of one price, with more aggressive adjustment generally occurring on the thinner market. The ratio of the NYSE price to the TSE price (an estimate of the spot exchange rate) is tightly distributed around the actual spot rate. The frequency of arbitrage opportunities is low, and the profits seldom exceed reasonable estimates of trading costs. In general, trading for more actively traded stocks exhibits stronger integration. Puzzlingly, NYSE order flow alone responds significantly to price deviations. This single market order flow response is at odds with the rest of our evidence, which favors integrated trading.
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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 | 0.005 | 0.010 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".