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Record W2080864312 · doi:10.1108/14757701011019835

The evaluation of the Canadian BAX contract in managing short‐term interest rate exposure

2010· article· en· W2080864312 on OpenAlexaffabout
John J. Siam, S. M. Khalid Nainar

Bibliographic record

VenueReview of Accounting and Finance · 2010
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Risk and Volatility Modeling
Canadian institutionsMcMaster University
Fundersnot available
KeywordsFutures contractInterest rateStylized factVolatility (finance)OriginalityContext (archaeology)EconomicsBusinessMonetary economicsFinancial economicsMacroeconomics

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to document stylized features and market behaviour of the Canadian Bankers' Acceptance Futures (BAX) contract; and outlook for the BAX contract as the dominant instrument to manage Canadian short‐term interest rate exposure. Design/methodology/approach The paper adopts GARCH methodology to model the time‐varying nature of the volatility of prices in the context of hedging and presents a time‐varying estimation of the hedge ratios between the BAX contract and major Canadian money market instruments. Findings The key finding is that the growth of the BAX Market hinges on the further development of the Canadian money market and its appeal to the international investor. Originality/value The paper demonstrates the suitability of the BAX contract as a tool in managing Canadian short‐term interest rate exposure for both domestic and international investors.

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)0.008
metaresearch head score (Gemma)0.028
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 score0.388
Threshold uncertainty score0.780

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.050
GPT teacher head0.277
Teacher spread0.227 · 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

Citations1
Published2010
Admission routes2
Has abstractyes

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