The Dynamic Linkages among Sector Indices: The Case of the Egyptian Stock Market
Bibliographic record
Abstract
<p>The main thrust of this study is to investigate both the long-term and short-term links among sectors of the Egyptian equity market. The empirical analysis is carried out using Johansen’s multivariate cointegration analysis and Granger’s causality analysis. The investigation period extends from 3 April 2011 to 31 May 2015. The results of cointegration analysis indicate that there exists a single cointegrating vector within the sample sector indices. The Granger’s causality analysis shows that the short-term causal relationships between the sector indices are substantially limited and, where they exist, practically unidirectional. By and large, an important implication of these findings is that there is still possibility to obtain gains from portfolio diversification in the short run. Nonetheless, investors with long-term horizon might not be able to benefit from diversifying into the various sectors of the Egyptian market.</p>
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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 | 0.001 | 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".