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Capital Flows and Hedge Fund Regulation

2009· article· en· W2002433399 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

VenueJournal of Empirical Legal Studies · 2009
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsYork University
Fundersnot available
KeywordsBusinessHedge fundFinanceCapitalizationOpen-end fundInvestment fundRobustness (evolution)Cost of capitalEconomicsMicroeconomicsInstitutional investorProfit (economics)Market liquidity

Abstract

fetched live from OpenAlex

This article introduces a cross‐country law and finance analysis of the regulatory impact on the level of capital flows and the sensitivity of capital flows in response to prior performance (i.e., the “flow‐performance” relationship) in the hedge fund industry. The data indicate that distribution channels in the form of wrappers (securities that combine different products) mitigate flow‐performance sensitivity. Distribution channels via investment managers and fund distribution companies enhance flow‐performance sensitivity. Funds registered in countries that have larger minimum capitalization requirements have higher levels of capital flows. Funds registered in countries that restrict the location of key service providers have lower levels of capital flows. Further, offshore fund flows and calendar effects evidenced in the data are consistent with tax factors influencing capital flows. The findings are robust to selection effects for offshore registrants, among other robustness checks.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.326
Threshold uncertainty score0.304

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 communication0.0000.001
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 head0.072
GPT teacher head0.313
Teacher spread0.241 · 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