MétaCan
Menu
Back to cohort

Real Estate for the Long Term: The Effect of Return Predictability on Long‐Horizon Allocations

2009· article· en· W2064706230 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueReal Estate Economics · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsReal estatePredictabilityReal estate investment trustEconomicsCapitalization rateCost approachFinancial economicsMean reversionTransaction costAsset allocationMonetary economicsInvestment (military)FinancePortfolioMathematics

Abstract

fetched live from OpenAlex

We examine how the predictability of real estate returns affects the risk of, and optimal allocations to, real estate for investors of differing investment horizons. Returns to direct real estate are mean reverting, and risk decreases with horizon. This is driven by a tendency for property transaction prices to overshoot inflation. Mean reversion in real estate returns is weaker than that of equities, resulting in real estate having similar risk to equities for long‐term investors. However, optimal portfolios have large allocations to direct real estate at all horizons, and the allocation increases with horizon. Finally, we find that real estate investment trusts are a redundant asset class for investors with access to direct real estate as an asset class, but they do have a role in optimal allocations when direct property investment is not feasible.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.723
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.018
GPT teacher head0.238
Teacher spread0.220 · 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