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Record W2522653566 · doi:10.1155/2016/8098092

External Monitoring and Dynamic Behavior in Mutual Funds

2016· article· en· W2522653566 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMathematical Problems in Engineering · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Markets and Investment Strategies
Canadian institutionsAcadia University
FundersScience Foundation of Ministry of Education of ChinaFundamental Research Funds for the Central UniversitiesEducation Department of Jiangxi ProvinceChina Postdoctoral Science FoundationMinistry of Education of the People's Republic of ChinaDepartment of Education of Liaoning ProvinceNational Natural Science Foundation of China
KeywordsInefficiencyBusinessMutual fundInformation asymmetryClosed-end fundFinanceInvestment (military)MicroeconomicsEconomicsMarket liquidity

Abstract

fetched live from OpenAlex

This paper studies the impact of external monitoring on the behavior in mutual funds. Specifically, we investigate how and why external monitoring can alleviate contracting inefficiency caused by information asymmetry between investors and the manager. It is shown that efficiency loss emerges when investors contract with the manager just relying on her investment return history. The establishment of external monitoring that provides investors more information about the manager’s ability can improve contracting efficiency, which converges to first-best as external monitoring strengthens. These results provide strong support for tightening supervision in mutual fund industry.

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.

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)0.000
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: Empirical
Teacher disagreement score0.342
Threshold uncertainty score0.413

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.022
GPT teacher head0.214
Teacher spread0.192 · 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