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Record W3122979850 · doi:10.1093/rapstu/rav005

Managerial Activeness and Mutual Fund Performance

2015· article· en· W3122979850 on OpenAlexaff
Hitesh Doshi, Redouane Elkamhi, Mikhail Simutin

Bibliographic record

VenueThe Review of Asset Pricing Studies · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Markets and Investment Strategies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPortfolioProxy (statistics)EconometricsWeightingVolatility (finance)Mutual fundEconomicsIntuitionInvestment managementActuarial scienceMathematicsFinancial economicsStatisticsPsychologyFinanceMarket liquidity

Abstract

fetched live from OpenAlex

A closet indexer is more likely to meet a value-weighted investment benchmark by value weighting the portfolio. Following this intuition, we introduce a simple measure of active management, the absolute difference between the value weights and actual weights held by a fund, summed across its holdings. This proxy captures managerial skill: active funds outperform passive ones by 2.5% annually. Compared with known measures of skill, our proxy robustly predicts fund flows, asset growth, factor-adjusted performance, and value added. Its predictive ability is orthogonal to that of other measures and is robust to controlling for volatility timing, past performance, and style. (JEL G10, G12, G14, G20, G23)

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.800
Threshold uncertainty score0.304

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.130
GPT teacher head0.305
Teacher spread0.175 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations147
Published2015
Admission routes1
Has abstractyes

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