Multiscale Analysis of International Linkages of REIT Returns and Volatilities
Bibliographic record
Abstract
This paper extends the REIT literature on international market linkages by introducing a time scale dimension. In particular, we apply the maximum overlap discrete wavelet transform (MODWT) to seven major global REIT markets, and investigate their linkages among returns and volatilities at different time scales. Our findings suggest strong scale-dependency of the market linkages. Specifically, the linkage among returns generally increases with time scale, implying that portfolio diversification is most efficient at short time horizons. Moreover, the return linkage is found to be time varying and its dynamics varies across scales. In addition, results on the volatility linkage, which manifests itself through volatility comovements and spillover, show that volatility comovements generally strengthen as scale increases and volatility spillover varies across scales in terms of strength and direction. Our findings cash doubt on the use of the scale-free correlation coefficient as a universal measure of market linkage. Our findings can be utilized by time-scale-conscious investors to improve portfolio selection and risk management.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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 | 0.000 |
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".