Bibliographic record
Abstract
In this study, we investi- gate whether the risk-Adjusted returns of a global REIT portfolio would be enhanced by adopting a trend following global strategy (which is an abso- lute concept sometimes known as absolute mo- mentum), a momentum-based strategy (which is a relative concept and requires individual country al- locations), or indeed a combination of the two. e examine the results in terms of both a dedicated global REIT exposure, and the impact on a multi- asset portfolio. We find that the main improve- ments arise when the broad index is replaced with one of the four trend following strategies. The port- folios deliver similar returns but volatility is re- duced by up to a quarter to the 8%-9% range, the Sharpe ratios increase by 0.1 to 0.5 with the main benefit being the reduction in the maximum draw- down to under 30% compared to 43% when the broad index was used. We thus find that a com- bined momentum and trend following a global REIT strategy can be beneficial for both a dedicated REIT portfolio and adding REITs to a multi-Asset portfolio.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".