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Record W3095599033 · doi:10.32479/ijefi.10610

THE DAY OF THE WEEK EFFECT: UNCONDITIONAL AND CONDITIONAL MARKET RISK ANALYSIS

2020· article· en· W3095599033 on OpenAlexaboutno aff
Olfa Chaouachi, Imen Dhaou

Bibliographic record

VenueInternational Journal of Economics and Financial Issues · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Markets and Investment Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsComposite indexNames of the days of the weekStock marketEconomicsIndex (typography)EconometricsStock market indexStock (firearms)Anomaly (physics)Risk–return spectrumFinancial economicsGeographyLinguisticsComposite indicator

Abstract

fetched live from OpenAlex

The objective of our investigation is to test empirically the existence of the day of the week effect on the Canadian stock market between September 2009 and August 2019. Our findings show that the day of the week effect is present. The highest and lowest mean daily returns of the S&P/TSX Composite index are detected on Tuesday and Monday, respectively. Moreover, we try to give an explanation of the day of the week effect by referring to the world market risk. Using unconditional and conditional models, our results reveal that only the significant Monday effect is still present after accounting for world market risk. Then, we can deduce that the Monday effect in returns of the S&P/TSX Composite index is not explained by the risk-return relationship and that it is an anomaly of the Canadian stock market.Keywords: Canadian stock market; Day of the week anomaly; Monday effect; World market risk.JEL Classification: G14DOI: https://doi.org/10.32479/ijefi.10610

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.629
Threshold uncertainty score0.355

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.013
GPT teacher head0.211
Teacher spread0.198 · 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 designTheoretical or conceptual
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

Citations5
Published2020
Admission routes1
Has abstractyes

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