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Effects of Daylight-Saving Time Changes on Stock Market Volatility: A Comment

2010· letter· en· W2474757176 on OpenAlexaff
Mark J. Kamstra, Lisa A. Kramer, Maurice D. Levi

Bibliographic record

VenuePsychological Reports · 2010
Typeletter
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Markets and Investment Strategies
Canadian institutionsUniversity of British ColumbiaUniversity of TorontoYork University
Fundersnot available
KeywordsStock marketEconometricsStock (firearms)AnxietyVolatility (finance)EconomicsOrdinary least squaresPsychologyNames of the days of the weekDaylightBehavioral economicsPsychiatryGeographyMicroeconomics

Abstract

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In a recent article in this journal, Berument, Dogan, and Onar (2010) challenged the existence of the previously documented daylight-saving effect. Kamstra, Kramer, and Levi's original finding (2000) was that average stock market returns on Mondays following time changes are economically and statistically significantly lower than typical Monday returns. Kamstra, et al. hypothesized that the effect may arise due to heightened anxiety or risk aversion on the part of market participants after they experience a 1-hr. disruption in their sleep habits, in accordance with prior findings in the psychology literature linking sleep desynchronosis with anxiety. Berument, et al. replicated the original findings using ordinary least squares estimation, but when they modeled the mean of returns using a method prone to producing biased estimates, they obtained puzzling results. The analysis here, based on standard, unbiased modeling techniques, shows that the daylight-saving effect remains intact in the U.S.

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 categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.445
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0020.002
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 head0.033
GPT teacher head0.251
Teacher spread0.218 · 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.

Study designNot applicable
Domainnot available
GenreCommentary

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

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