قیاس مخاطر الاستثمار في الأسواق المالیة وتأثیرها على سلوك المستثمرین
Bibliographic record
Abstract
Abstract: This study aims to analyse investment risks nature and sources in Islamic FinancialProducts and its Ethical counterpart arising from its investing, and also to demonstrate theimpact of their performance and risks measuring on the investor's behavior. Secondly, ThePerformance analysis method is used to compare the two selected benchmarks chosen fromamong the (DJIM) family of the Canadian Stock Market, utilising daily data of the close pricesof the Islamic index (CANI) and its Ethical counterpart (CAN) covering the period from(January 2005 to December 2015). The results show that the Islamic index (CANI) outperformand was more volatility sensible than its Ethical counterpart (CAN), particularly during theperiod of the Sub-prime Crisis in 2008. Finally, the analysis of the correlation rate shows thatthere was no significant link between the studied indices and US (T-Bill), which denies theexistence of the benchmark price risk. The study affords some of recommendations amongthem: improving the competitiveness in the Islamic Financial Markets (a), by using ModernInformation Systems (b) and the independence of Shariah Boards of Islamic Banks (c), tomanage and hedge risks.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.044 | 0.012 |
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".