Passive in Name Only: Delegated Management and 'Index' Investing
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
This Article provides the first detailed empirical analysis of the landscape of U.S. stock market indices. First, I hand collect detailed information about the universe of indices used as benchmarks for U.S. mutual funds. I document substantial heterogeneity across indices and find that the overwhelming majority of the indices in my sample are used as a primary benchmark by only a single fund. I then turn to “passive” index funds and find that both these phenomena are even more extreme among the indices that these funds track. Far from being “passive,” my findings indicate that index investing is better understood as a form of delegated management, where the delegee is the index creator rather than the fund manager. Finally, I turn to ETFs and find that a substantial fraction of these funds track indices that they or their affiliates create. Even controlling for other factors, I find that these funds have, on average, higher expense ratios. My findings shed light on an overlooked part of the financial market and have substantial implications for investor protection.
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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 | 0.000 | 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