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Record W2175289477 · doi:10.19030/iber.v9i10.635

Global Mutual Fund Industry Comparisons: Canada, The United Kingdom And The United States

2010· article· en· W2175289477 on OpenAlexaboutno aff
Brian D. Fitzpatrick, Daniel C. Hepp, Erinn J. Lott

Bibliographic record

VenueInternational Business & Economics Research Journal (IBER) · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicPrivate Equity and Venture Capital
Canadian institutionsnot available
Fundersnot available
KeywordsMutual fundKingdomEquity (law)Closed-end fundFund of fundsBusinessFinanceEconomicsPolitical science

Abstract

fetched live from OpenAlex

The concept of mutual funds is older than many believe, originating in Holland over 230 years ago. Through the years, mutual funds have evolved by allowing investors to invest their capital in various venues. The structure of mutual funds in Canada, the United Kingdom, and the United States possess similar configurations. The majority of funds in all three nations are invested in the equity market. Although the structure may be the same, the size in terms of assets varies by these three countries. This is not the only difference though; the expense ratio is greatly differentiated, dramatically affecting the amount of return that the investor will anticipate over time. Assuming identical returns, the authors illustrate that over a hypothetical ten-year time period, your funds would grow the most in the United States, followed by the United Kingdom and finally Canada. This analysis assumes comparable contemporary expense ratios of 1.4% for the United States, 1.63% for the United Kingdom, and 2.1% for Canada. In addition, we make the assumption that these comparison countries are having investors procure funds in no-load mutual funds.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.683
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0000.002
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 head0.089
GPT teacher head0.331
Teacher spread0.242 · 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.

Study designNot applicable
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

Citations1
Published2010
Admission routes1
Has abstractyes

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