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Record W149794494

Electronic trading, liquidity and information efficiency : evidence from the Montreal exchange

2007· dissertation· en· W149794494 on OpenAlexaboutno aff
Kunyi Wang

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2007
Typedissertation
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Markets and Investment Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsElectronic tradingOpen outcryMarket liquidityAlternative trading systemFutures contractAlgorithmic tradingBusinessTrading turretEquity (law)Electronic marketsFinancial economicsFlash tradingDark liquidityEconomicsThe InternetFinanceComputer science
DOInot available

Abstract

fetched live from OpenAlex

This paper studies the deviation spread of the Equity Index S&P/TSX 60 Futures Contract SXF's daily price from the Cost of Carry Model before and after the contract is launched on the electronic trading platform in the Montreal Exchange. The relative stability of the deviation spread after the introduction of electronic trading shows strong market efficiency improvement. Besides this, after examining the relationship of the deviation spread with the trading volume and some other information sources generated on the trading venue before and after the introduction of the electronic trading, it is found that electronic trading greatly mitigates these information sources' adverse impacts on the spread's stability. This empirical evidence suggests that the information efficiency facilitated by the electronic trading may not conflict with the liquidity enhancement in the public exchange organization.

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)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.743
Threshold uncertainty score0.510

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.035
GPT teacher head0.255
Teacher spread0.220 · 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 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
Published2007
Admission routes1
Has abstractyes

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