Effects of Daylight-Saving Time Changes on Stock Market Volatility: A Comment
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.039 | 0.030 |
| Insufficient payload (model declined to judge) | 0.005 | 0.006 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".