CAN WE BEAT THE “BUY-AND-HOLD” STRATEGY? ANALYSIS ON EUROPEAN AND AMERICAN SECURITIZED REAL ESTATE INDICES
Why this work is in the frame
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Bibliographic record
Abstract
The aim of this paper is to use the Shiryaev-Zhou index to examine the performances of securitized real estate indices of four countries: US, UK, Canada and Germany. The result reveals that the Shiryaev-Zhou index is a leading indicator and can act as a predictor on certain securitized real estate indices. Furthermore, our results show that the trading strategy we constructed according to the Shiryaev-Zhou index generally outperforms the “buy-and-hold” strategy under the assumption of no transaction costs. The stronger the predictive power of the Shiryaev-Zhou index is, the larger extent our trading strategy beats the “buy-and-hold” strategy. This is useful in strategic property management that property practitioners can follow our strategy to trade real estate stocks/funds in order to increase their profits.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it