Fund Flows and Performance - A Study of Canadian Equity Funds
Bibliographic record
Abstract
We study the behavior of mutual fund investors with a specific focus on fund flows - performance relationship. Using a comprehensive survivorship bias free sample of Canadian open-end equity mutual funds and panel data analysis we find evidence of a rational response of fund flows to upside and downside performance changes. Unlike the findings on US funds and investors, we find that investors neither chase winners nor hang on to losing funds. While investors do allocate funds based on past performance the allocations do not disproportionately in favor star funds. Poor performers experience significant fund withdrawals. Combined with the evidence on a positive association of returns variability with fund flows this fund flow performance relationship shows that the fund incentive structure is not biased towards greater risk taking by fund managers. The size of the fund family and previous fund allocations are also significant in influencing decisions on future fund allocations. We also show lack of short and longterm performance persistence. Inspite of the evidence on a rational response the returns realized by investors are lower than the returns reported by mutual funds suggesting poor ability to time the market.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".