The Effect of Investment Horizons on Risk, Return and End-of-Period Wealth for Major Asset Classes in Canada
Bibliographic record
Abstract
Abstract The objective of this paper is to investigate whether the current practice among financial planners of recommending stocks at an early age and progressively moving into cash or bonds as retirement approaches would be appropriate. We computed returns, risks and end-of-period wealth distributions of various Canadian asset classes at increasing horizons between 1957 and 2003, based on the bootstrapping technique. Results show that investment outcomes at short horizons can be quite different from outcomes at longer horizons. Evidence is provided in favour of time diversification, while the current market practice of life cycle investing is not fully supported as stocks continue to exhibit more favourable risk-return payoffs than other asset classes, even at shorter time intervals. Résumé Cet article se propose d'étudier le bien-fondé de la pratique actuelle qui consiste à recommander des actions aux investisseurs dans leur jeunesse et l'argent liquide ou les obligations lorsqu'ils approchent l'âge de la retraite. Grâce à la technique de bootstrapping, nous calculons les retours sur investissement, les risques et la distribution de richesse en fin de période pour plusieurs types d'actifs canadiens à horizons divers entre 1957 et 2003. Les résultats présentent des différences importantes entre les investissements à court terme et les investissements à long terme. Les données disponibles soutiennent l'idée de la diversification temporelle et réfutent partiellement la pratique actuelle du cycle de vie d'investissement. De fait, les actions comportent toujours un profil risques-bénéfices plus favorable que les autres types d'actifs, même pour des intervalles de temps réduits.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".