Bibliographic record
Abstract
In this paper we analyzed the violations of UIP for the Swiss Franc against the Dollar, the Euro, the Yen, the Pound and the Canadian Dollar using recent data up to fall 2008. This exercise provides the following main results : first the Swiss interest rate puzzle disappeared, i.e. mean returns on Swiss Franc assets are no longer systematically and significantly lower (as in the 1980 – 1998 sample) when compared jointly with other major currencies in the 1999 to 2008 period. Second and in contrast to earlier evidence we failed to find evidence that geopolitical crises lead to an appreciation of the Swiss Franc in the last ten years. Third even the short run validity of UIP cannot be rejected for the Swiss Franc against the five currencies for the 1999 – 2008 sample. Unfortunately our attempt to locate the time of change and the currencies involved by the application of tests for structural breaks with unknown break point did not lead to clear cut conclusion for the Euro and the Dollar, the two most important foreign currencies from a Swiss perspective.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".