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Record W2184313206

FLOATING MARGIN RATES S&P/TSX 60 BASKET OF INDEX SECURITIES AND INDEX PARTICIPATION UNITS

2005· article· en· W2184313206 on OpenAlexaboutno aff
Jacques Tanguay

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicInsurance and Financial Risk Management
Canadian institutionsnot available
Fundersnot available
KeywordsIndex (typography)Margin (machine learning)Volatility (finance)Floating interest rateCapitalization-weighted indexEconomicsEconometricsStock market indexInterest rateMonetary economicsComputer scienceHistory
DOInot available

Abstract

fetched live from OpenAlex

Paragraph k) of article 9001 of the Rules of Bourse de Montreal Inc. (the Bourse) provides for a monitoring and adjustment mechanism of the floating margin rates that are applicable to index securities baskets or index participation units when the volatility of the closing prices of the index exceeds the margin rate set for such index. If the volatility of an index exceeds the floating margin rate that has been established for such index, the floating margin rate is then adjusted consequently for a minimum of twenty (20) working days from the date on which the approved participants are advised of such an adjustment. At the end of this twenty (20) working days period, the floating margin rate is then readjusted at a lower level if regulatory margin intervals calculations indicate a reduction of these intervals. In reason of the recent volatility of the S&P/TSX 60 index, it is necessary to increase the floating margin rate applicable to baskets of index securities and index participation units related to the S&P/TSX 60 index. This new floating margin rate is effective immediately for a minimal period of twenty (20) working days as mentioned above and it replaces those which had been established in circular no. 144-2005 published by the Bourse on October 5, 2005.

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)0.006
metaresearch head score (Gemma)0.026
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: Other
Teacher disagreement score0.023
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.026
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.003
Science and technology studies0.0010.001
Scholarly communication0.0070.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0230.015

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 head0.030
GPT teacher head0.234
Teacher spread0.203 · 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

Citations0
Published2005
Admission routes1
Has abstractyes

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