MétaCan
Menu
Back to cohort
Record W2013874583 · doi:10.2753/ree1540-496x460407

Trading Behavior on Expiration Days and Quarter-End Days: The Effect of a New Closing Method

2010· article· en· W2013874583 on OpenAlexaboutno aff
Yu Chuan Huang, Shu Hui Chan

Bibliographic record

VenueEmerging Markets Finance and Trade · 2010
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Markets and Investment Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsClosing (real estate)Market liquidityQuarter (Canadian coin)ExpirationMonetary economicsFutures contractEconomicsExpiration dateFinancial economicsBusinessStock (firearms)FinanceMedicine

Abstract

fetched live from OpenAlex

On July 1, 2002, the Taiwan Stock Exchange changed its closing price procedure to a five-minute call auction. This paper examines different types of trader behavior at the close before and after institution of the new mechanism. The results show that, since the new mechanism was introduced, individuals have shifted their trades away from the closing interval to the preclosing interval, which worsens market liquidity at the close. This paper also finds that institutional investors try to influence closing prices for window dressing at quarter ends, whereas foreign institutions attempt to influence closing prices on the expiration days of index futures. After the new mechanism's introduction, neither the expiration-day effect nor the quarter-end-day effect disappeared. Despite this finding, the new mechanism does make it more difficult and costly for traders to attempt to influence the stock price.

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)0.002
metaresearch head score (Gemma)0.016
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 score0.002
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.249
Teacher spread0.229 · 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

Citations10
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueEmerging Markets Finance and TradeSame topicFinancial Markets and Investment StrategiesFrench-language works237,207