A Comparative Analysis of the Performance of Collective Investment Institutions
Bibliographic record
Abstract
Pension plans and mutual funds represent a substantial part of the welfare systems in both Europe and Spain. One of the most important factors in the choice of a plan or fund is its performance, since if high returns are obtained; the participant will receive higher payments when the contingency covered by the plan occurs or when the investors of the mutual funds recover their investments. The main objective of this paper is therefore to analyze the performance of Spanish collective investment institutions. To this end, we apply a multi-index model based on an extension of Jensen?s Alpha to a sample of data corresponding to 466 collective investment institutions for the period between February 2007 and February 2011. The results obtained show that the performance of Spanish pension plan and mutual fund managers is, in general, close to zero. This suggests that in the Spanish pension plan and mutual fund market, the value added by active management does not compensate for its associated costs. On the other hand, pension plan and mutual fund performance improves slightly when fees are not deducted, and positive risk-adjusted returns are obtained in some cases. In general, the mutual fund industry performs better than the pension plan industry.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".