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Record W2071386202 · doi:10.1002/cjas.29

The investment nature of income trusts and their role in diversified portfolios

2007· article· en· W2071386202 on OpenAlexafffundvenue
Sean Cleary, Greg MacKinnon

Bibliographic record

VenueCanadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l Administration · 2007
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Markets and Investment Strategies
Canadian institutionsSaint Mary's University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsBondFixed incomeStock (firearms)PortfolioEconomicsFinancial economicsAsset allocationExcess returnMonetary economicsBusinessEconometricsFinance

Abstract

fetched live from OpenAlex

Abstract We examine the investment characteristics of income trusts to explore their role within a portfolio as well as to clarify the on‐going political debate surrounding income trusts. Results show that income trusts exhibited risk‐adjusted performance that far outperformed equities and bonds during our sample period. We adopt a multifactor return generating process for ex‐post income trust returns to quantify the degree to which they are influenced by bond‐ and stock‐related effects. The relationship between trust returns and bond returns is very weak, whereas the relationship between trust returns and stock returns is quite strong. We conclude that while income trusts appear indistinct from equities as an asset class, they significantly expand the efficient set. Copyright © 2007 ASAC. Published by John Wiley & Sons, Ltd.

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)0.003
metaresearch head score (Gemma)0.021
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.054
GPT teacher head0.265
Teacher spread0.211 · 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
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

Citations6
Published2007
Admission routes3
Has abstractyes

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