Bibliographic record
Abstract
Exchange Traded funds are the fastest growing investment product in capital markets today. Total funds deployed in ETFs are approaching US$700 billion globally which is nearly 15 per cent of $4.5 trillion held in traditional equity mutual funds. This study examines the risk-reward of 74 Canadian ETFs across three major sponsors representing nearly $29 Billion in assets under management for the last 5 years (out of which, the last two years - 2007 and 2008 - witnessed a general decline of the Canadian stock market). The study found the best performing ETFs were international funds especially emerging market funds which witnessed high growth rates in the last decade (especially BRIC countries). Currency-hedged funds also performed relatively better reflecting the role of exchange rates in impacting the returns of cross-border investments. Commodity ETFs generally had shown mixed results: the bear commodity ETFs (reflecting the macro-economic performance) generally did well as compared to bull commodity ETFs. In terms of risk-reward, the results are somewhat different. International and emerging market ETFs performed well in terms of positive and high alphas (excess returns) but also had displayed relatively high risk. In terms of risk-reward, the Canadian and US broad equity ETFs performed well (Treynor ratio of 0.11) while fixed income ETFs had the lowest Treynor ratio (-2.05). In terms of ranking, the currency-hedged ETFs performed relatively better than Canadian sector ETFs. The international and emerging market funds while displaying positive Treynor ratios (risk-reward) were the ETFs with relatively modest performance. --P. iii.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".