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Record W1978973742 · doi:10.1002/bref.133

Mortgage-backed securities in Canada: the size of the market and prospects for the future

2005· article· en· W1978973742 on OpenAlexaffabout
Jane Londerville

Bibliographic record

VenueBriefings in Real Estate Finance · 2005
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsDebtCommercial mortgage-backed securityFinancial systemSecurity marketFinancial marketSecondary mortgage marketEconomicsBusinessFinanceMortgage insurance

Abstract

fetched live from OpenAlex

Mortgage-backed securities (MBS) were introduced into the Canadian financial system in 1987. This paper describes their development and history, and compares these with the situation in other countries, through a brief review of mortgage securitisation in various parts of the world (the UK, Australia and Japan). The primary uses of MBS in Canada and positive aspects of securitisation are explored, both as they have been experienced since the inception of MBS in the late 1980s and as they relate to the basic structure of the mortgage finance system in place before MBS were introduced. The paper also contrasts the MBS markets in the USA and Canada. The proportion of national mortgage debt that is packaged into MBS in both countries is examined, and the paper discusses reasons for the significantly smaller proportion of debt in Canadian MBS versus the numbers for the USA. Future prospects for growth in the Canadian MBS market are explored. Copyright © 2005 Henry Stewart Publications

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)0.003
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 score0.054
Threshold uncertainty score0.390

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0030.002
Scholarly communication0.0060.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.009
GPT teacher head0.182
Teacher spread0.173 · 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

Citations4
Published2005
Admission routes2
Has abstractyes

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