REITs in a Mixed-Asset Portfolio:<i>An Investigation of Extreme Risks</i>
Why this work is in the frame
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Bibliographic record
Abstract
Until the recent financial crisis, it was widely believed that adding real estate investment trusts (REITs) to a mixed-asset portfolio expanded the efficient frontier and provided superior risk-adjusted returns. More recent evidence suggests that REITs may have higher volatility, Value at Risk (VaR), and expected shortfall (ES) than equities in times of increased market volatility, precisely when the stabilizing properties of REITs are most desirable. This study expands on the emerging literature with two contributions. First, it examines the impact of REITs on the VaR of a portfolio of stocks and bonds over the last two decades. Second, a new, more accurate method of estimating VaR, Conditional Autoregressive Value at Risk (CAViaR), is used. The more accurate VaR estimates show that adding REITs to the portfolio has no significant impact on VaR until after the financial crisis begins. After the financial crisis begins, adding REITs to a portfolio of stocks and bonds dramatically increases VaR. The results have significant implications for portfolio selection. <b>TOPICS:</b>Real estate, mutual funds/passive investing/indexing, VAR and use of alternative risk measures of trading risk, portfolio construction
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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 | 0.002 | 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 | 0.001 |
| Open science | 0.001 | 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