Performance of US and European Exchange Traded Funds: A Base Point-Slack-Based Measure Approach
Why this work is in the frame
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Bibliographic record
Abstract
This study evaluates the performance of United States (US) and European Exchange Traded Funds (ETFs) using the non-oriented version of the base point-slack-based measure (BP-SBM) Data Envelopment Analysis (DEA) model, which allows for handling negative data that can arise in some of the metrics traditionally used in this type of analysis. Our findings show that US efficient ETFs are considered benchmarks more often than European efficient ETFs. Nonetheless, it was possible to conclude that European inefficient ETFs were generally less inefficient than US ETFs. Our findings also show that ETFs’ efficiency (particularly for US ETFs) in the short run is more related to risk than to profitability factors. This implies that as the time horizon lengthens, the importance of profitability factors for the ETFs’ financial performance grows.
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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 | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 it