The Effect of Financial Leverage on Corporate Performance of Some Selected Companies in Nigeria
Bibliographic record
Abstract
This paper empirically examines the effect of financial leverage on selected indicators of corporate performance in Nigeria. In an attempt to juxtapose the earlier findings that were specific of developed nations, econometric technique of Vector Auto Regression (VAR) model was employed. The findings revealed that Leverage shocks exert substantially on corporate performance in Nigeria. In addition, Earnings Per Share (EPS) depends more on feedback shock and less on leverage shock. Leverage shocks on Earnings Per Share indirectly affect the Net Assets Per Share of firms as the bulk of the shocks on the Net Assets Per Share was received from Earnings Per Share of the firms. Leverage therefore significantly affect corporate performance in Nigeria. Thus, theories that are adequate for indigenous macro economic variables should be developed instead of depending on the structured theories of the advanced developed countries of the world, as these theories cannot be appropriate proxies for advancing the course of the developing nations. Key words: Financial Leverage; Corporate Performance; Earnings Per Share (EPS); Net Assets Per Share (NARS); Leverage Stocks; Capital Structure; Vector Auto Regression Model (VAR) Resume Cet article examine de facon empirique l’effet de levier financier sur les indicateurs selectionnes de la performance des entreprises au Nigeria. Dans une tentative de juxtaposer les resultats anterieurs qui etaient specifiques des pays developpes, la technique econometrique de regression automatique Vector (VAR) a ete employee. Les resultats ont revele que les chocs de levier exercent essentiellement sur la performance des entreprises au Nigeria. En outre, le benefice par action (EPS) depend de plus sur le choc des commentaires et moins sur le choc de levier. Chocs de levier sur le benefice par action indirecte sur les actifs nets par action des entreprises comme la majeure partie des chocs sur les actifs nets par action a ete recue de benefice par action des entreprises. L’effet de levier consequent affecter significativement les performances de l’entreprise au Nigeria. Ainsi, les theories qui sont adequates pour les autochtones variables macroeconomiques devraient etre developpees au lieu de dependre des theories structurees des pays avances du monde, que ces theories ne peuvent pas etre procurations appropriees pour faire avancer le cours des nations en developpement. Mots cles: Effet de levier financier; Rendement organisationnel; Benefice par action; Actif net par action; Les stocks de levier; La structure du capital; Modele de regression du Vecteur Auto
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".