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Record W2311011372

Low Volatility Investing in U.S. Equity REITs

2017· article· en· W2311011372 on OpenAlexaff
Greg MacKinnon, Jon Spinney

Bibliographic record

VenueJournal of the Asian Real Estate Society · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsVolatility (finance)Real estate investment trustFinancial economicsEquity (law)PortfolioEconomicsVolatility risk premiumVolatility smileVolatility swapReal estateImplied volatilityEconometricsMonetary economicsBusinessFinance
DOInot available

Abstract

fetched live from OpenAlex

We examine the market for U.S. equity real estate investment trusts (REITs) for evidence of the volatility effect, in which low volatility stocks tend to outperform high volatility ones, as has been found in the general equity market by prior research. While there is some evidence of a volatility effect in the first ten years of the sample, this disappears in a more recent time period. Furthermore, we test the efficacy of low risk portfolio construction techniques and find that none perform any better than a market cap weighted portfolio ¡V although they are also no worse ¡V over any of the time periods examined. Thus, there is no evidence that using a risk-based portfolio design that emphasizes low volatility would improve portfolio performance for a REIT allocation.

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 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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.198
Threshold uncertainty score0.414

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.050
GPT teacher head0.275
Teacher spread0.225 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2017
Admission routes1
Has abstractyes

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