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Wyszukujesz frazę "failure prediction" wg kryterium: Temat


Wyświetlanie 1-2 z 2
Tytuł:
Decision tree based model of business failure prediction for Polish companies
Autorzy:
Durica, Marek
Frnda, Jaroslav
Svabova, Lucia
Powiązania:
https://bibliotekanauki.pl/articles/19090954.pdf
Data publikacji:
2019
Wydawca:
Instytut Badań Gospodarczych
Tematy:
decision trees
prediction model
financial ratios
business failure
Polish companies
Opis:
Research background: The issue of predicting the financial situation of companies is a relatively young field of economic research. Its origin dates back to the 30's of the 20th century, but constant research in this area proves the currentness of this topic even today. The issue of predicting the financial situation of a company is up to date not only for the company itself, but also for all stakeholders. Purpose of the article: The main purpose of this study is to create new prediction models by using the method of decision trees, in achieving sufficient prediction power of the generated model with a large database of real data on Polish companies obtained from the Amadeus database. Methods: As a result of the development of artificial intelligence, new methods for predicting financial failure of the company have been introduced into financial prediction analysis. One of the most widely used data mining techniques in this field is the method of decision trees. In the paper, we applied the CART and CHAID approach to create a model of predicting the financial difficulties of Polish companies. Findings & Value added: For the creation of the prediction model, a total of 37 financial and economic indicators of Polish companies were used. The resulting decision trees based prediction models for Polish companies reach a prediction power of more than 98%. The success of the classification for non-prosperous companies is more than 83%. The created decision tree-based prediction models are useful mainly for predicting the financial difficulties of Polish companies, but can also be used for companies in another country.
Źródło:
Oeconomia Copernicana; 2019, 10, 3; 453-469
2083-1277
Pojawia się w:
Oeconomia Copernicana
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Logit business failure prediction in V4 countries
Autorzy:
Durica, Marek
Valaskova, Katarina
Janoskova, Katarina
Powiązania:
https://bibliotekanauki.pl/articles/125652.pdf
Data publikacji:
2019
Wydawca:
Politechnika Białostocka. Oficyna Wydawnicza Politechniki Białostockiej
Tematy:
logit
business failure
financial ratio
prediction model
V4 countries
funkcja logitowa
niepowodzenie biznesowe
wskaźnik finansowy
model prognostyczny
kraje V4
Opis:
The paper presents the creation of the model that predicts the business failure of companies operating in V4 countries. Based on logistic regression analysis, significant predictors are identified to forecast potential business failure one year in advance. The research is based on the data set of financial indicators of more than 173 000 companies operating in V4 countries for the years 2016 and 2017. A stepwise binary logistic regression approach was used to create a prediction model. Using a classification table and ROC curve, the prediction ability of the final model was analysed. The main result is a model for business failure prediction of companies operating under the economic conditions of V4 countries. Statistically significant financial parameters were identified that reflect the impending failure situation. The developed model achieves a high prediction ability of more than 88%. The research confirms the applicability of the logistic regression approach in business failure prediction. The high predictive ability of the created model is comparable to models created by especially sophisticated artificial intelligence approaches. The created model can be applied in the economies of V4 countries for business failure prediction one year in advance, which is important for companies as well as all stakeholders.
Źródło:
Engineering Management in Production and Services; 2019, 11, 4; 54-64
2543-6597
2543-912X
Pojawia się w:
Engineering Management in Production and Services
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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