Models predicting corporate financial distress and industry specifics

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21630%2F19%3A00334905" target="_blank" >RIV/68407700:21630/19:00334905 - isvavai.cz</a>
Result on the web
<a href="http://itise.ugr.es/ITISE2019_vol1.pdf" target="_blank" >http://itise.ugr.es/ITISE2019_vol1.pdf</a>
DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Models predicting corporate financial distress and industry specifics
Original language description
This paper is focused on tools predicting corporate financial situation. There have been constructed plenty of models whose aim is to predict possible corporate default or distress. These models will be examined. Traditionally analyses would be focused on the explanatory power or models' accuracy. The aim of this paper is different. Although the models can be mainly used generally there are many specifics which affect results and gained conclusions. The specific highlighted in this paper is an industry branch. Companies operate in different industry areas which influence their performance and overall financial results and ratios and therefore it has an impact on the models' result. The paper works with three industry branches: Manufacture of fabricated metal products, except machinery and equipment (CZ-NACE 25), Manufacture of machinery and equipment (CZ-NACE 28) and Construction (CZ-NACE F). The results will be based on three data sample, specifically financial healthy companies 2012, insolvent companies 2012 and companies 2017. The results of different models predicting financial distress will be computed and compared. The main tools of descriptive statistics will be applied. It should prove or disapprove if industry specifics influence the models significantly.
Czech name
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Czech description
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Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of Papers ITISE 2019 International Conference on Time Series and Forecasting
ISBN
978-84-17970-78-9
ISSN
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e-ISSN
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Number of pages
10
Pages from-to
647-656
Publisher name
Godel Impresiones Digitales S.L.
Place of publication
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Event location
Granada
Event date
Sep 25, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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