MétaCan
Menu
Back to cohort
Record W2353165263

Study on the effect of the institutional investor based on the quarterly time window

2011· article· en· W2353165263 on OpenAlexaboutno aff
Miu Shi-ling

Bibliographic record

VenueEconomic Research Guide · 2011
Typearticle
Languageen
FieldDecision Sciences
TopicStock Market Forecasting Methods
Canadian institutionsnot available
Fundersnot available
KeywordsInstitutional investorStock marketBusinessCapital marketStock (firearms)Sample (material)Agency (philosophy)ChinaQuarter (Canadian coin)Agency costMonetary economicsFinanceEconomicsCorporate governance
DOInot available

Abstract

fetched live from OpenAlex

Agencies of the capital market investor has become the leading force,on the stock market is.Choosing a company of china stock market for the sample data,through the establishment of a quarter of the institutional investor for the conduct of the regression model.research institutions and the stock investors in the same period,the return and analysis of the agency actions,not the return of strength.Study found that the changes in institutional investors to be the reward is with lagtime a significant impact,this is a persistent and more influence in the current issue of relatively weak,the issue of an agency action in response.based on the result of securities market,health,stability,efficient operation of a few suggestions.

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)0.014
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 score0.008
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.396
GPT teacher head0.479
Teacher spread0.083 · 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
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueEconomic Research GuideSame topicStock Market Forecasting MethodsFrench-language works237,207