Bibliographic record
Abstract
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.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".