Detail publikačního výsledku

The choice of the type of image for graphical processing of input data for corporate bankruptcy prediction using CNN

ŠEBESTOVÁ, M.; DOSTÁL, P.

Originální název

The choice of the type of image for graphical processing of input data for corporate bankruptcy prediction using CNN

Anglický název

The choice of the type of image for graphical processing of input data for corporate bankruptcy prediction using CNN

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

This paper deals with the application of Convolutional Neural Networks (CNN) for the bankruptcy prediction of firms in the Czech Republic. It proposes several variants based on the GoogLeNet architecture that predict the bankruptcy of a company 1 to 3 years in advance. The inputs of the model are financial ratios whose values are converted into several types of images. The various types of images are searched to improve the accuracy of company bankruptcy prediction and the right type of image is found. CNN networks can effectively distinguish between active and bankrupt enterprises. The predictive accuracy of the best proposed model ranges between 85 and 93% (depending on the number of years before bankruptcy).

Anglický abstrakt

This paper deals with the application of Convolutional Neural Networks (CNN) for the bankruptcy prediction of firms in the Czech Republic. It proposes several variants based on the GoogLeNet architecture that predict the bankruptcy of a company 1 to 3 years in advance. The inputs of the model are financial ratios whose values are converted into several types of images. The various types of images are searched to improve the accuracy of company bankruptcy prediction and the right type of image is found. CNN networks can effectively distinguish between active and bankrupt enterprises. The predictive accuracy of the best proposed model ranges between 85 and 93% (depending on the number of years before bankruptcy).

Klíčová slova

bankruptcy prediction, convolutional neural network, financial indicators

Klíčová slova v angličtině

bankruptcy prediction, convolutional neural network, financial indicators

Autoři

ŠEBESTOVÁ, M.; DOSTÁL, P.

Rok RIV

2022

Vydáno

07.09.2021

Nakladatel

VSB - Technical University of Ostrava

Místo

Ostrava

ISBN

978-80-248-4548-7

Kniha

Financial Management of Firms and Financial Institutions

Strany od

164

Strany do

172

Strany počet

9

BibTex

@inproceedings{BUT172817,
  author="Monika {Šebestová} and Petr {Dostál}",
  title="The choice of the type of image for graphical processing of input data for corporate bankruptcy prediction using CNN",
  booktitle="Financial Management of Firms and Financial Institutions",
  year="2021",
  pages="164--172",
  publisher="VSB - Technical University of Ostrava",
  address="Ostrava",
  isbn="978-80-248-4548-7"
}