Benchmarking Measures of Investment Performance with Perfect-Foresight and Bankrupt Asset Allocation Strategies
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Bibliographic record
Abstract
It is well known that popular measures of investment performance do not agree on the relative performance of passive portfolios, professionally managed funds, or various asset allocation strategies. In this article, the author shows that the problems are more fundamental. It benchmarks the performance measures against bankrupt asset allocation strategies that lose everything and perfect-foresight asset allocation strategies that yield returns beyond anyone9s wildest dreams. Unbelievably, the risk-adjusted performance of some bankrupt strategies exceeds the risk-adjusted performance of all the perfect-foresight strategies! This occurs because the measures are based on average arithmetic returns which completely miss the fundamental importance of bankruptcy. Supplementing the measures with analyses of accumulated wealth, compound returns, or continuously compounded returns would alleviate the problem. <b>TOPICS:</b>Mutual fund performance, accounting and ratio analysis, statistical methods
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 it