Effect of Corporate Financial Leverage on Financial Performance: A Study on Publicly Traded Manufacturing Companies in Bangladesh
Bibliographic record
Abstract
The study strives to examine the effect of financial leverage on financial performance in a developing country context using two OLS regression models based on panel data consisting of 816 cases (48 companies x 17 years). Financial performance is measured using ROA, ROE, EPS, and Tobin’s Q, and financial leverage is measured using the debt-assets ratio and debt-equity ratio. It is observed that ROA and Tobin’s Q are negatively correlated with financial leverage, which is in line with the assumptions of the pecking order theory, market timing theory, and many empirical studies. However, financial leverage has a positive effect on ROE and no effect on EPS. These results are also consistent with the MM theorem, static trade off theory and many other empirical studies. Yet again, the two OLS models have put forward conflicting results while taking EPS as the dependent variable. The results corroborate the inefficient use of debt capital and suggest the need to improve the reliability of accounting information.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".