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The identification of indicators influencing the credit risk if automotive companies in the Czech Republic

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dc.title The identification of indicators influencing the credit risk if automotive companies in the Czech Republic en
dc.contributor.author Kameníková, Blanka
dc.contributor.author Daňová, Radka
dc.contributor.author Urbánek, Tomáš
dc.relation.ispartof Proceedings of Feb Zagreb 12th International Odyssey Conference on Economics and Business, 2021
dc.identifier.issn 2671-132X Scopus Sources, Sherpa/RoMEO, JCR
dc.date.issued 2021
utb.relation.volume 3
dc.citation.spage 612
dc.citation.epage 621
dc.event.title 12th International Odyssey Conference on Economics and Business (FEB)
dc.event.location Zagreb
utb.event.state-en Croatia
utb.event.state-cs Chorvatsko
dc.event.sdate 2021-06-09
dc.event.edate 2021-06-12
dc.type conferenceObject
dc.language.iso en
dc.publisher Univ Zagreb, Fac Economics & Business
dc.subject automotive en
dc.subject rating en
dc.subject credit risk en
dc.subject aspect global rating model en
dc.subject panel data regression en
dc.description.abstract The paper deals with the credit risk and identification of indicators, which influence the rating of automotive companies in the Czech Republic. Methods used in this study were correlation analysis, descriptive statistics and panel data regression. The aim of this paper was firstly to calculate the ratings of automotive companies in the Czech Republic utilizing the Aspect Global Rating model and then determine, which indicator has the highest influence on rating of tested companies. The Aspect Global Rating model consists of seven indicators: operating margin, return on equity, depreciation coverage indicator, prompt liquidity, self-financing indicator, return on operating assets, and assets turnover ratio. When using the Aspect Global Rating model, the research results indicate that the company's rating is statistically dependent on the value of the depreciation coverage indicator. The depreciation coverage indicator was proven to have the highest impact on the rating. After that, the data was subjected to panel data regression and three models were created. Proposed models solved the dependency between the depreciation coverage indicator and rating. First model tested hypothesis, that rating of the company is not dependent on the depreciation coverage indicator, whereas second model tested, whether rating is dependent on the depreciation coverage indicator and last model was focused on the dependency between rating and tested indicator when the time component was considered. The comparison of models has shown that there is a statistically significant difference between model 1 and model 2 and the rating is statistically dependent on the value of the depreciation coverage indicator. There is a similar situation between model 2 and model 3. There is a statistically significant difference and the rating is dependent on time. Automotive companies should focus on the depreciation coverage indicator, as it is ascertained from research that it has the most significant impact on values of rating. en
utb.faculty Faculty of Management and Economics
dc.identifier.uri http://hdl.handle.net/10563/1012190
utb.identifier.obdid 43882956
utb.identifier.wok 001230124200044
utb.source C-wok
dc.date.accessioned 2025-01-15T08:08:16Z
dc.date.available 2025-01-15T08:08:16Z
dc.description.sponsorship [RO/2018/10]
utb.contributor.internalauthor Kameníková, Blanka
utb.contributor.internalauthor Daňová, Radka
utb.contributor.internalauthor Urbánek, Tomáš
utb.fulltext.sponsorship This paper was supported by the research project RO/2018/10 - Identification of risks and their impact on sectoral and corporate innovation and finance performance, risk management in the digital economy.
utb.wos.affiliation [Kamenikova, Blanka; Danova, Radka] Thomas Bata Univ Zlin, Fac Management & Econ, Dept Finance & Accounting, Mostni 5139, Zlin 76001, Czech Republic; [Urbanek, Tomas] Thomas Bata Univ Zlin, Fac Management & Econ, Dept Stat & Quantitat Methods, Mostni 5139, Zlin 76001, Czech Republic
utb.fulltext.projects RO/2018/10
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