Bibliographic record
Abstract
This study measures the performance of unit trusts in Malaysia by focusing on the selection abilities of fund managers in their effort to give better return to the investors. There were 41 equity unit trusts funds used as a sample for 120 months that is from 1995 until 2004. This study considers heteroscedasticity problems and therefore, the findings had been separated into two parts that is before and after correcting for heteroscedasticity problem. Negative selectivities are observed in ten funds before the adjustment of heteroscedasticity whereas when this problem has been corrected, there are eleven funds that show negative selectivities. The findings give an indication that the unit trusts funds in Malaysia are not able to give a better return to investors. Some of the fund managers do not have an ability to do better than those managers that are using the naive buy and hold strategy. This result is consistent to Shamsher et al. (2000), Firth (1997), Chang and Lewellen (1985) and Henriksson (1984), who conclude that the fund managers did not have an ability to select securities that can provide returns that are more than the market returns.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 | 0.001 |
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".