Firm Value and Profitability of Saudi Arabian Companies Listed on Tadawul: Moderating Role of Capital Structure
Bibliographic record
Abstract
The impact of profitability on firm value was always been a matter of great interest for financial managers, because the objective of a company is to increase its value and on the other hand the investors expect higher returns on their investment.Therefore, the purpose of present research is to investigate the impact of profitability on firm value moderated with capital structure in different Saudi Arabian companies.The profitability is measured in terms of ROA (Return on Assets) and ROE (Return on Equity), firm value is calculated using Tobin's Q.Capital structure is measured with the debt-equity ratio.The study selects different companies listed on Tadawul as a sample and the study period starts in 2013 and ends in 2020.To analyze the data collected from the annual reports of listed companies, the study reports results by employing panel regression with FE and RE model, and panel GMM.The analyzed results report a positively significant impact of profitability on firm value and a negative and significant effect of capital structure on firm value in all the estimated models.Further, the capital structure interacts as a moderator between profitability and firm value, where the study finds a negatively significant effect of profitability on firm value after moderation.The results strengthen the moderation of capital structure between profitability and firm value.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".