Effect of Some Firms’ Internal Factors on Value in Emerging Markets: Evidence from the Egyptian Stock Market
Bibliographic record
Abstract
1- Abstract - The study aims to test the relation between internal factors of firm & performance of stock price by using Cross-section regression that depends on Yuenan Wang, Amalia Di Lorio (2007) and Fama & Macbath (1973) throughout the period from Jan – 2003 to Dec – 2007, while providing evidence from the Egyptian stock market. The researcher reached certain results: there is a positive relation between Beta and stock return, Beta measure is inappropriate and then CAPM is inappropriate in the Egyptian stock market. In addition, the researched found a positive relation between Earning to price ratio and stock return and a negative relation between dividend to price ratio, Liquidity ratio, debit ratio and stock return. This article consists of a Literature Review, Study Data, Methodology, Empirical Study, Analysis and Interpretation of Results, Conclusion and Recommendations.
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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 | 0.004 | 0.002 |
| 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 | 0.002 |
| 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".