Unraveling the multiscale comovement of green bonds and structural shocks: An oil-driven analysis
Bibliographic record
Abstract
This paper examines the multiscale comovement between the green bonds issued in developed countries and international oil-driven shocks. We extracted the oil shocks using a structural vector autoregressive model. The countries in our analysis comprised the UK, the US, Japan, Canada, Australia, and Europe, with the data being captured from November 28, 2008 to June 11, 2021. We applied the wavelet technique to examine the returns comovement across time and frequency as a form of bivariate and multivariate analysis. Our results highlight a limited connection between the returns of green bonds and the international oil market, with Norway and Sweden exhibiting strong comovement across low frequencies. We posit that during crisis periods, the correlation between green bond returns and oil returns varies. The findings of this study have several implications for policymakers and investors with an interest in both oil futures and green bonds.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".