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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".