The Directive on Alternative Investment Fund Managers: Comparative Analysis of Certain Aspects of the Regulatory Regimes of Europe, Canada and the United States of America
Bibliographic record
Abstract
The Alternative Investment Fund Managers Directive ("AIFMD"), adopted by the European Union on 11 November 2010, has introduced a harmonized set of rules for alternative investment funds (“AIFs”) in Europe. This thesis discusses potential financial risks for the AIFs industry arising from the European regulatory reform, which started before the current financial crisis, and compares relevant European, Canadian and US rules governing AIFs. This comparative analysis is based on four main criteria: i) registration and authorization requirements, ii) general financial transparency requirements, iii) capital requirements, and iv) remuneration restrictions. The analysis of AIFs regulatory reform in Europe leads to three main conclusions. First, the AIFMD requirements are much stricter than analogue regimes in Canada and the United States. Second, as a consequence of this regulation, European AIFs may be in disadvantage. Third, the complexity of the present European institutional framework is not able to fully implement the European regulatory reform.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".