Impact of Financial Disruption on Firms’ Performance (An Event Study)
Bibliographic record
Abstract
This study aims to estimate the effect of financial disruption on the performance of pharmaceutical companies listed on Bombay Stock Exchange. The total number of listed pharmaceutical companies on Bombay Stock Exchange is 153 companies, 32 companies were excluded due to non-availability of the quarterly financial reports. Three variables have been taken for exploring the impact of financial disruption on the firms’ performance which are: net sales, net profit and earning per share. Data were extracted from interim quarterly financial reports retrieved from the Prowess Q database. Two steps of analysis have been conducted using EViews. First, comparing firm’s performance pre disruption period second quarter (September, 2016) with firm’s performance post disruption period third quarter (December, 2016). Second, comparing the firms’ performance post disruption, third quarter (December, 2016) with the same quarter (December, 2015). Descriptive statistics and paired sample T-test were applied to evaluate the effect of the financial disruption on firms’ performance. The findings reveal that the financial disruption has no statistically significant impact on the performance of the pharmaceutical companies at level of 5%.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".