Financial performance of the selected Indian pharmaceutical companies: An empirical analysis
Bibliographic record
Abstract
The Indian Pharmaceutical Industry has gained tremendous momentum during the last few decades. Considering its importance both in the social sector and in the economy of our country a study has been endeavored to analyze the nature and movement of Return on Equity (ROE) of 9 selected companies listed in National Stock Exchange (NSE) in India during a period of 15 years from 2006-07 to 2020-21. This analysis has been conducted using DuPont. Step Regression has been used to measure to explain ROE by its predictors such as Operating Profit Margin (OPM), Interest Expense Ratio (IER), Assets Turnover Ratio (ATR), Tax Retention Ratio (TRR) and Equity Multiplier (EM). Study shows a substantial relationship between ROE and OPM in case of large cap companies. But most of the mid and small cap companies have shown a different relationship where other predictors such as ATR, TRR and EM are proved to be significant to explain ROE.
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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 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".