Models predicting corporate financial distress and industry specifics

Kód výsledku v 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>

Výsledek na webu

<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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Jazyk výsledku

angličtina

Název v původním jazyce

Models predicting corporate financial distress and industry specifics

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Models predicting corporate financial distress and industry specifics

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

50204 - Business and management

Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

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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Počet stran výsledku

10

Strana od-do

647-656

Název nakladatele

Godel Impresiones Digitales S.L.

Místo vydání

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Místo konání akce

Granada

Datum konání akce

25. 9. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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