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Record W3203048170 · doi:10.53383/100081

International Real Estate Review

2007· article· en· W3203048170 on OpenAlexafffundabout
Lawrence Kryzanowski, Margarita Tcherednitchenko

Bibliographic record

VenueInternational Real Estate Review · 2007
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsConcordia University
FundersSocial Sciences and Humanities Research Council of CanadaConcordia University
KeywordsReal estate investment trustEquity (law)Diversification (marketing strategy)Risk–return spectrumInitial public offeringBusinessComposite indexReal estatePortfolioFinancial economicsMonetary economicsStock market indexInvestment performanceEconomicsStock marketFinanceStock exchangeReturn on investmentGeography

Abstract

fetched live from OpenAlex

The return performance and factor sensitivities of Canadian equity real estate investment trusts (E-REITs) are examined. Today, typical and average Canadian E-REIT IPOs are correctly priced based on first- day and subsequent short-run returns. The overpricing evident earlier in the 1993-96 period for typical and average E-REIT IPOs has corrected. E-REITs are equity investments with about one-half the market risk, and greater ensitivity to interest-rate changes, than the S&P/TSX Composite Index. E-REITs outperformed the S&P/TSX Composite over the 1996-2004 period on a return, risk, and market- and/or risk-adjusted basis. Thus, E-REITs provided material diversification benefits with no sacrifice in return, when added to a common stock portfolio during the studied period.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.074
Threshold uncertainty score0.249

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.005
Science and technology studies0.0000.000
Scholarly communication0.0030.002
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0740.030

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.

Opus teacher head0.038
GPT teacher head0.299
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations1
Published2007
Admission routes3
Has abstractyes

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