Bibliographic record
Abstract
The Canadian REIT sector has experienced rapid growth that has coincided with the strong performance of the real estate sector. Thus, this thesis examines the risk-adjusted return performance in the secondary and primary (IPO) markets and interest rate sensitivity of all non-mortgage REITS that traded on the TSX during the 1996-2004 period. Smaller REITs offer lower risk-adjusted returns since the value-weighted REIT index has about the same mean monthly return but much lower standard deviation than its equally-weighted counterpart. Based on the Sharpe ratio and the Jensen alphas, both equally- and value-weighted REIT indexes outperform the market. Although mean first-day unweighted and size-weighted IPO returns are significant and negative, the size-weighted counterparts are approximately equal to the commissions saved by new issue versus secondary market purchase. Mean mispricing in the first and not second subperiod suggests that earlier overpricing of IPOs has corrected, and that more recent REIT IPOs are approximately correctly priced on average. Consistent with studies of US REITs, Canadian REITs do not outperform (or underperform) the market during the year after initial issue. If past performance is reflective of what can be expected in the future, REITs provide investors with a "fairly" priced vehicle for participating in real estate investment. REITs are more interest-rate sensitive than other equities but the sensitivity depends upon the interest rate change proxy used. REIT returns are inversely related with bond premia. This interest-rate sensitivity has implications for the management of risk for this asset class within an investor's 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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".