Análise do Capital de Giro das Empresas Listadas na B3 Frente à Crise Econômica Brasileira
Bibliographic record
Abstract
In this article, we aim to analyze if there were changes in the working capital of publicly-traded companies in the context of the Brazilian Economic Crisis. We based on the variables and financial structures of the Dynamic Model of Financial Management of a sample of 89 companies whose shares did list in B3. We considered the period from the second quarter of 2011 to the first quarter of 2017. Half of this period corresponds to before the Brazilian Economic Crisis, and half corresponds to during this crisis. Using 2,136 balance sheet data, we calculated the variables of the Dynamic Model and identified the six financial structures of this approach. We have analyzed changes in the percentages of companies classified in each of these structures. We have advanced by statistically evaluating whether significant differences occurred in each of the components of the Dynamic Model during the crisis. The results show that, during the crisis, there was a subtle worsening in the working capital situation of the companies, although we have observed that this occurs in specific variables of the Dynamic Model. The financial and operating accounts of the working capital should tend to exhibit different dynamics when the companies faced the context of crisis.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".