An Empirical Investigation of the Day-of- the-Week Effect on Stock Returns and Volatility: Evidence from Muscat Securities Market
Bibliographic record
Abstract
This paper investigates the anomalous phenomenon of the day-of-the-week effect on Muscat securities market. The study uses a sample that covers the period from 1 December 2005 until 23 November 2011. It also utilizes a nonlinear symmetric GARCH (1,1) model and two nonlinear asymmetric models, TARCH (1,1) and EGARCH (1,1). The empirical findings provide evidence of no presence of the day-of-the-week effect. However, unlike other developed markets, Muscat stock market seems to start positive and ends also positive with downturn during the rest of the trading days. In addition, the parameter estimates of the GARCH model (a and b ) suggest a high degree of persistent in the conditional volatility of stock returns. Furthermore, the asymmetric EGARCH, and TARCH models show no significant evidence for asymmetry in stock returns. The study concludes that Muscat securities market is an efficient market.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".