Exploring the Resilience of Islamic Stock in Indonesia and Asian Markets
Bibliographic record
Abstract
This study aims to investigate the relationship between returns and risk of Islamic stock under stable economic conditions, crises, and pandemics within the scope of Indonesian and Asian Islamic capital markets. How do economic conditions affect the risks and returns of investors in the Indonesian and Asian Islamic capital markets? Verification of the veracity of the Islamic capital market serves as a more resilient option for alternative investments. This study uses Granger causality to determine exogenous and endogenous variables when building the model. The model that is formed is then analyzed using regression with dummy variables of stable economic conditions, crises, and pandemics. The first research findings on differences in crisis, stable and pandemic times in the Asian stock market show that there is no significant difference in effect between stable times and during a crisis, but there are differences in the effect during stable and pandemic times. The second research finding states that the return on Asian market Shariah stocks has no influence on increasing or reducing the value of risk or value at risk. The third finding explains that Islamic stocks in Indonesia have a greater risk value during pandemics and crises than in stable times, but the effect of pandemic and crisis conditions is not as great as Islamic stocks in Asia as a whole. In order to stabilize markets and reduce risks, regulatory bodies and governments frequently employ a variety of actions during times of crisis. When applied to trading volume, risk, and return patterns, these findings can help determine the appropriate policy.
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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 | 0.000 |
| 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".