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Record W3125992945 · doi:10.3905/jii.2014.5.2.057

Market Reactions to Changes in the S&P/TSX SmallCap Index

2014· article· en· W3125992945 on OpenAlexaffabout
Ernest N. Biktimirov, Boya Li

Bibliographic record

VenueThe Journal of Index Investing · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Markets and Investment Strategies
Canadian institutionsBrock University
Fundersnot available
KeywordsEquity (law)Index (typography)EconomicsStock (firearms)Index fundFinancial economicsMonetary economicsFinanceInstitutional investorLawPolitical scienceComputer science

Abstract

fetched live from OpenAlex

Stocks added to major indexes generally experience positive abnormal returns. However, researchers disagree on whether these abnormal returns are permanent or temporary, and offer competing explanations. We examine stock price and trading volume reactions to changes in the Canadian S&P/TSX SmallCap Index. Our primary finding is that significant changes in prices and trading volume occur for stocks added to or deleted from the S&P/TSX SmallCap Index. The effect depends on whether a stock is a pure addition or deletion as opposed to being shifted between S&P/TSX indexes. TOPICS:Mutual funds/passive investing/indexing, fundamental equity analysis, developed

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)0.000
metaresearch head score (Gemma)0.007
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 score0.149
Threshold uncertainty score0.295

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.062
GPT teacher head0.240
Teacher spread0.178 · 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
Published2014
Admission routes2
Has abstractyes

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