A Longitudinal and Cross-Industry Study on the Stability of Financial Ratios of Malaysian Companies
Bibliographic record
Abstract
The purpose of this study is to test whether a set of six financial ratios that have been used extensively by practitioners and researchers and found to be useful for various purposes including company financial performance evaluations are stable across three different industry sectors and whether they are stable over time. The sample comprises a total of 180 listed companies covering a period of five years from 2006 to 2010. Analysis of variance and post hoc multiple comparisons were carried out for each ratio to see whether it exhibits a stable profile across industries and over time. The findings showed that four out of the six ratios displayed no significant differences across industries, one (Current Assets Turnover) showed significant differences among all three sectors while the remaining ratio (Cash Flow to Total Assets) showed significant differences between two of the sectors. The test results also showed that all the financial ratios except for Cash Flow to Total Assets for all three industry sectors are stable over time. This finding is surprising in that the years 2008 and 2009 are periods where the financial crisis is at its height and companies’ financial data are expected to be adversely affected and where the means of the ratio values in these two years are expected to be volatile and unstable compared to the period before and after the financial crisis. The analysis also showed that there are no interaction effects between sector and time. Thus, some ratios are industry specific and some ratios cannot be extrapolated over time when evaluating financial performance or forecasting future trends.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".