An Empirical Investigation of Islamic Calendar Effect in Global Islamic Equity Indices
Bibliographic record
Abstract
This study aims to explore the effect of Islamic Months specifically Ramadan and Zil-Haj on the stock returns and volatility of the Islamic Global Equity Indices. For the said purpose, the data on three Global Equity Islamic Indices including; Dow Jones Islamic Market World Index, MSCI ACWI Islamic Index, and S&P Global BMI Shariah Index are collected from 5th Jan 2011 (1st Muharram 1432 A.H.) to 12th November 2015 (30th Muharram 1437 A.H.). Ordinary Least Square (OLS) and GARCH (1,1) regression methods are applied to analyze the impact of the Islamic months on global stock returns and volatility respectively. Empirical results reveal significant negative impact of Zil-Haj on returns and volatility of Islamic Global Equity Indices. However, no significant impact of Ramadan on returns and volatility of Islamic Global Equity Indices are revealed. These findings will be fascinating and of utmost interest amidst the researchers, investors and practitioners.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".