Is the research agenda for calendar anomalies “much do about nothing”?
Bibliographic record
Abstract
Calendar anomalies are a class of financial market phenomena which links \nperiodic, time-specific dummy variables and variations in the market price of an asset. Prior studies which report a calendar anomaly are seen by some as refutations of the efficient market hypothesis. In this paper, we estimate, test for the presence of, and find no evidence of, the day-the-week effects in the S&P 500, 2013-2023. That is, in this paper, we show that the daily-dummy variables (both individually and collectively) are independent of the S&P 500. This finding supports those who have argued that the day�the-week effects, and (by extension) all calendar anomalies, are “chimera delivered by intensive data mining” or, quite simply, such anomalies are “much ado about nothing.”
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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 | 0.023 | 0.085 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.014 | 0.029 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.037 | 0.012 |
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".