MétaCan
Menu
Back to cohort
Record W2773820807 · doi:10.5430/ijfr.v9n1p1

Monday Effect in the Chinese Stock Market

2017· article· en· W2773820807 on OpenAlexvenueno aff
Gerardo Alfonso

Bibliographic record

VenueInternational Journal of Financial Research · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Markets and Investment Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsThursdayMainland ChinaStock marketChinaNames of the days of the weekEquity (law)Stock (firearms)Stock market indexEconomicsFinancial economicsBusinessGeographyPolitical science

Abstract

fetched live from OpenAlex

The Monday effect is a well know effect in some countries around the world. The Monday effect is the observation that stock returns on Monday are statically significantly lower than for the rest of the days of the week. There is no obvious fundamental reason behind this occurrence and if it actually exists it might be due to human behavioral patterns. This Monday effect observation originated in the U.S. several decades ago and it has since being observed in several other countries. In this article the occurrence of the Monday effect is analyzed in the mainland China equity market. It was found that for the period from 2011 to 2016 there was no statistically significant Monday effect but interestingly there are indications of a possible Thursday effect. This concept was tested with several market indexes covering the two major mainland China stock exchanges (Shanghai and Shenzhen). These indexes covered also a broad spectrum of company sizes. The ChiNext index, which is a Nasdaq like type of index for the Chinese market, was also included. In this article it was also tested and confirmed that the returns on Chinese equities, as expected, do not follow a normal distribution.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation 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 score0.307
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.066
GPT teacher head0.370
Teacher spread0.304 · 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 teacher head, 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

Citations9
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Financial ResearchSame topicFinancial Markets and Investment StrategiesFrench-language works237,207