The Impact of Sustainable Investing on Financial Performance
Bibliographic record
Abstract
This research project investigates the impact of sustainable investing on financial performance within the Egyptian market, focusing on a selected group of twelve companies listed on the Egyptian Exchange (EGX) that meet predetermined environmental, social, and governance (ESG) criteria. The study addresses the gap in the existing literature by examining the specific relationship between sustainable investment and financial performance in the Egyptian context, within the period of 2018 to 2022. Regression models employed to examine the statistical association between sustainable investment practices and financial performance indicators, while correlation analysis helps to identify the strength and direction of the relationship. Revenue Growth and Total Debt to Equity were used as control variables. The main results of the research project state that there is an impact of sustainable investment on some financial performance of the Egyptian companies listed in ESG index. Study results show that there is no significant relationship between ESG factors and some indicators like current ratio, cash ratio, operating cash flow, debt ratio, turnover ratio, gross margin ratio, Tobin Q, and assets growth. However, it showed that there is a positive correlation between corporate social responsibilities (CSR) or ESG factors and financial performance measures like return on assets (ROA), return on equity (ROE), and return on sales (ROS).
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".