Foreign exchange risk exposure of Canadian domestic, exporting and multinational firms : market and industry effects on bilateral and multilateral exchange rates
Bibliographic record
Abstract
The failure of most previous research to support the widely accepted hypothesis of an existing relationship between exchange rate movements and stock returns is primarily attributed to research design drawbacks. In the present study we address the research design problem from a relatively new perspective, suggesting changes to the market index variable and to the exchange rate variable. We use monthly stock returns for the 1971-1999 period to estimate overall exchange rate exposure of Canadian domestic and exporting companies to trade weighted multilateral exchange rates and to the Canada-U.S. bilateral exchange rate. The results show no significant exposure of the domestic firms sample, suggesting indirect exposure may be limited. However significant exposure effects are found for the exporting sample. In general, these results do not suggest that there are any benefits from using the more (theoretically) appealing industry specific exchange rates and the purely domestic index in studying the exposure to the multilateral exchange rates. Yet benefits from using the purely domestic index do exist when studying the exposure to the Canada-U.S. bilateral exchange rate. We also examine the determinants of currency exposure for a set of Canadian multinational corporations. To this end we decompose our companies' exposure into a foreign sales variable, a foreign production variable, and a market concentration variable. All coefficients have the expected signs, although only foreign sales and foreign production are found to be significant. These results are contingent on the exchange rate proxy used--specifically significance is found only when industry specific rates are employed. In light of this result we hypothesize the existence of an industry effect . This industry effect captures industry specific trade flows components (foreign sales and foreign production)
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".