A Short Note on the Potential for a Momentum Based Investment Strategy in Sector ETFs
Bibliographic record
Abstract
The focus of this research is on the enhanced one-year average annual return performance of Select Sector SDPR EFFs with the highest average annual realized return over the previous five-year period [MaxRet strategy]. From 2004 through 2015, the MaxRet strategy generates a higher average annual total return than an equal weight portfolio [EW strategy] of the same sector funds. The average annual return for the MaxRet strategy is 14.13% compared to 9.75% for the EW strategy. In addition, the coefficient of variation [CV] for the MaxRet and EW strategies are 1.52 and 1.59 respectively. The MaxRet strategy, therefore, is a more efficient strategy in that it generates less standard deviation risk per unit of average annual return than the EW strategy over the study period. Measures of downside risk further support the enhanced out-of-sample performance of the MaxRet strategy.
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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".