New Evidence On Hedge Fund Performance Measures
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Hedge funds are still relatively unfamiliar to most investors despite the intense popularity they have enjoyed in recent years. Measuring the performance of these financial instruments using traditional methods is, however, problematic, since their returns do not follow a normal distribution. In this study, we consider rankings obtained with the Stochastic Dominance (SD) method and compare them with ranks produced using Sharpe Ratios, Modified Sharpe Ratios, and Data Envelopment Analysis. We also explore the advantages highlighted by the literature of the Data Envelopment Analysis (DEA) method in relation to traditional measures like Sharpe ratio and Modified Sharpe ratio. Our results show that classic performance measures are better correlated with SD than DEA results.
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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 | 0.014 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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