A Wavelet-Based Analysis of the Co-Movement between Sukuk Bonds and Shariah Stock Indices in the GCC Region: Implications for Risk Diversification
Bibliographic record
Abstract
Investors are interested in knowing whether sukuk bonds and shariah stock indices in the Gulf Corporation Council (GCC) region are related. This study examines the connectedness between the sukuk- and shariah-compliant stock indices in the GCC financial markets. Bivariate and multivariate wavelet approaches are applied to the daily data covering the period 10 July 2008 to 15 May 2017. The empirical findings demonstrate a strong correlation between these GCC sukuk bond indices and shariah stock indices. The degree of connectedness between these sukuk and shariah stock indices varies across time and scale. A strong and positive association is observed in the short term and a negative association is evident in the long term. The same findings are observed, using the wavelet cohesion approach that also validates the existence of portfolio diversification opportunities at a short-time horizon. The multivariate cross-correlation analysis reveals that these sukuk and shariah stock markets are highly integrated across time and scale. Furthermore, the value at risk (VaR) for the sukuk bond–shariah stocks portfolio is performed to highlight the significance of the wavelet analysis. The outcomes show that portfolio stocks are variable with respect to time or scale (time diversification). Overall, analyzing the sukuk bond–shariah stock index returns in the GCC at a multiscale level makes it easier for financial agents dealing with heterogeneous trading horizons to assess the benefits of diversifications.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".