Safe haven government bonds: Identification using a regime-switching copula model
Why this work is in the frame
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Bibliographic record
Abstract
The purpose of this paper is to identify safe haven government bonds against domestic stock markets and against internationally diversified stock portfolios.We develop a two-state regime-switching copula model that describes various patterns of the stock-bond return dependence structure and apply it to eight developed countries (Australia, Canada, France, Germany, Japan, Switzerland, the United Kingdom, and the United States) for the period 1999 to 2018.We find that government bonds of all of the countries (except for Canada) qualify as safe havens for domestic stock markets.However, for international stock portfolios, only US government bonds were a safe haven for the entire period while German, Japanese, and UK government bonds served as safe havens for certain limited periods.The decomposition analysis shows that the correlation between local currencies and international stock markets is an important factor in determining safe haven government bonds against international stock portfolios.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it