The performance of metal-related funds before and during covid-19: Evidence from Brazil
Why this work is in the frame
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Bibliographic record
Abstract
The main purpose of this paper is to analyze the risk-adjusted performance of Brazilian commodity metal-related funds considering the Covid-19 pandemic. The database is comprised of Brazilian investment funds during the period from January, 2005 to June, 2021. Using daily returns, each quarter, we employed the Return Based Style Analysis to identify metal-related funds. The study hypothesis was tested through panel data regressions. On one hand, the main results suggest that, during Covid-19 pandemic, metal-related funds performed better in comparison to the other investment funds. This result was also persistent considering different measures for fund performance. On the other hand, the performance of metal-related funds was equivalent to the performance of the other funds during the Global Financial Crisis. The quantitative analysis also considers the effects of number of confirmed cases for Covid-19 and total vaccination on fund’s daily returns.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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