Distribuční vlastnosti finančních ukazatelů: případ českých konkurzních údajů
| dc.contributor.author | Karas, Michal | |
| dc.contributor.author | Režňáková, Mária | |
| dc.coverage.issue | 13 | cs |
| dc.coverage.volume | VII | cs |
| dc.date.accessioned | 2014-01-14T14:47:14Z | |
| dc.date.available | 2014-01-14T14:47:14Z | |
| dc.date.issued | 2013-03 | cs |
| dc.description.abstract | Purpose of the article: The purpose of this paper is to analyse the distributional properties of financial data, suitable for building a bankruptcy forecast model, in the sense of normality deviation and the existence of outliers. Methodology/methods: In praxis, financial data in the form of financial ratios is very often not normally distributed. A Shapiro-Wilk’s procedure was used to test normality (Shapiro, Wilk, 1965) and a Box-Cox transformation (Box, Cox, 1964) for normalizing financial ratios. Scientific aim: We would like to contributed to the previous pieces of research in following ways. Firstly, by analysing a greater range of accounting ratios or indicators (i.e. 44), secondly, by focusing on data of a different character (data suitable for building a bankruptcy forecast model), thirdly, by explaining cases in which the parameter l is not possible to estimate, and finally fourthly, identifying a possible cause of transformation failure in achieving normality of financial ratios. Findings: Before the transformation none of the analysed financial ratios met the condition of one-dimensional normality, not even on the 1-% level. After transformation, the condition of one-dimensional normality was met, at the 1-% level, by 34% of the analysed financial ratios. The same condition, but at the 5 or 10-% level, was met by 27% of the analysed financial ratios. The parameter l was not possible to estimate in the case of 18% of financial ratios. Conclusions: The condition of normality for untransformed Czech bankruptcy data seems almost as impossible to fulfil. This conclusion implies the use of non-parametric methods, such as artificial neural networks. However, the comparison of the parametric method’s performance using untransformed or transformed data is the subject of further research. | en |
| dc.format | text | cs |
| dc.format.extent | 56-67 | cs |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.citation | Trendy ekonomiky a managementu. 2013, VII, č. 13, s. 56-67. ISSN 1802-8527. | cs |
| dc.identifier.issn | 1802-8527 | |
| dc.identifier.uri | http://hdl.handle.net/11012/24420 | |
| dc.language.iso | en | cs |
| dc.publisher | Vysoké učení technické v Brně, Fakulta podnikatelská | cs |
| dc.relation.ispartof | Trendy ekonomiky a managementu | cs |
| dc.relation.uri | http://www.fbm.vutbr.cz/cs/fakulta/vedecky-casopis/aktualni-cislo/1649-trendy-ekonomiky-a-managementu-cislo-13-rocnik-vii | cs |
| dc.rights | © Vysoké učení technické v Brně, Fakulta podnikatelská | cs |
| dc.rights.access | openAccess | en |
| dc.subject | bankruptcy | en |
| dc.subject | financial ratios | en |
| dc.subject | outlier detection | en |
| dc.subject | normality | en |
| dc.subject | data transformation | en |
| dc.title | Distribuční vlastnosti finančních ukazatelů: případ českých konkurzních údajů | cs |
| dc.title.alternative | The Distributional Properties of Financial Ratios: The Case of Czech Bankruptcy Data | en |
| dc.type.driver | article | en |
| dc.type.status | Peer-reviewed | en |
| dc.type.version | publishedVersion | en |
| eprints.affiliatedInstitution.faculty | Fakulta podnikatelská | cs |