A TEORIA DA SINALIZAÇÃO E A RECUPERAÇÃO JUDICIAL: UM ESTUDO NASEMPRESAS DE CAPITAL ABERTO LISTADAS NA BM&FBOVESPA
Based on the Theory of Signs, this work began with the assumption that the financial indicators emit signals about some economic-financial situations. When using a bankruptcy prediction model, works with the hypothesis that the problems of an organization can be detected in advance, thus identifying...
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| Autores principales: | , , , |
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| Formato: | article |
| Lenguaje: | PT |
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Universidade Regional do Noroeste do Estado do Rio Grande do Sul
2018
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| Materias: | |
| Acceso en línea: | https://doi.org/10.21527/2237-6453.2018.42.553-584 https://doaj.org/article/13ebcb5b1cad4145913836294c1e24a7 |
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| Sumario: | Based on the Theory of Signs, this work began with the assumption that the financial indicators emit signals about some economic-financial situations. When using a bankruptcy prediction model, works with the hypothesis that the problems of an organization can be detected in advance, thus identifying the financial health of the company. Thus, the purpose of this article is to identify the financial indicators that signal the bankruptcy of state organizations. We selected all public companies listed on the BM & FBovespa during the period 2005-2013, a total of 330 companies and 2,664 observations. Data were grouped (pooled) of unbalanced way and the parameters estimated by econometric technique logistic regression (logit). The results showed that four indicators are statistically significant for bankruptcy prediction, and the contents of Current Liquidity, Asset Productivity and Return on Assets significant at 1% and Return on Equity significant 5%. Furthermore, the estimated model classified correctly 93.69% of the observations, however, only to the level of the percentage of solvent companies prediction is satisfactory, reaching 100%. Although the model does not provide a satisfactory forecast percentage for companies in bankruptcy, the individual results presented for each of them (significances and regression coefficients) were statistically significant. |
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