Rebalancing strategies and the performance of balanced portfolios: 1925–2001
Bibliographic record
Abstract
The results of a study of the performance of balanced portfolios in South Africa over the last 77 years are presented. Using the asset classes South African equities, bonds and cash, five portfolios of widely varying composition were formed. In addition two portfolios containing a portion of the equity allocation in the US market were created. Three rebalancing periods of a month, a quarter and a year and a strategy of rebalancing whenever the equity proportion of the portfolio moved more than five percentage points from its target were tested. The compound annual returns of the portfolios were largely unaffected by the choice of rebalancing period. A small increase in portfolio standard deviation was found as the rebalancing period increased. In the absence of transactions costs it appears that an annual rebalancing strategy would have been the best choice. However annual rebalancing resulted in large deviations in the portfolio equity proportions during the rebalancing period, particularly for portfolios with low proportions of equity.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".