Debt Policy and Corporate Performance: Empirical Evidence from Tehran Stock Exchange Companies
Bibliographic record
Abstract
The ability of companies in determining suitable financial policies to make investment opportunities is one of the most principal factors for the companies’ growth and progression. Adopting a debt policy or a capital structure is considered as a momentous decision that influences the companies’ value. This paper is aimed to investigate the probable relationship between debt policies (including Current Debt, Non-Current Debt, and Total Debt) and performance of Tehran Stock Exchange Companies. The regression model is applied to investigate the relationship between the performance indicators and debt ratios. In this research, financial performance indicators are considered as Gross Margin Profit, Return on Assets (ROA), Tobin's Q Ratio, and Debt Ratios (Current Debt, Non-Current Debt, and Total Debt). “size” and “growth rate” are considered as control variables. Results show that an increase in current debts, non-current debts, and total debts has a negative influence on the corporate performance. It was also found that companies that merely attempt to create assets through debts, without any attention to the company size and other important factors, are not able to have an excellent performance.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".