Bankruptcy or success? The effective prediction of a company's
financial development using LSTM

J 2020

Bankruptcy or success? The effective prediction of a company's financial development using LSTM

VOCHOZKA, Marek, Jaromír VRBKA and Petr ŠULEŘ

Basic information

Original name

Bankruptcy or success? The effective prediction of a company's financial development using LSTM

Name in Czech

Bankrot nebo úspěch? Efektivní predikce finančního rozvoje společnosti pomocí LSTM

Authors

VOCHOZKA, Marek (203 Czech Republic, guarantor, belonging to the institution), Jaromír VRBKA (203 Czech Republic, belonging to the institution) and Petr ŠULEŘ (203 Czech Republic, belonging to the institution)

Edition

Sustainability, Basel, Switzerland, MDPI, 2020, 2071-1050

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

50200 5.2 Economics and Business

Country of publisher

Switzerland

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

URL

RIV identification code

RIV/75081431:_____/20:00001825

Organization unit

Institute of Technology and Business in České Budějovice

DOI

http://dx.doi.org/10.3390/su12187529

Keywords (in Czech)

bankrotní modely; společnost; dlouhodobá krátkodobá paměť (LSTM - long short-term memory); neuronové sítě (NN); predikce; úspěch

Keywords in English

bankruptcy models; company; long short-term memory (LSTM); neural networks (NN); prediction; success

Abstract

ORIG CZ

V originále

The objective of this contribution is to create a methodology for the identification of a company failure (bankruptcy) using artificial neural networks with at least one long short-term memory (LSTM) layer. A bankruptcy model was created using deep learning, for which at least one layer of LSTM was used for the construction of the NN. For the purposes of this contribution, Wolfram's Mathematica 13.

In Czech

Cílem tohoto příspěvku je vytvořit metodiku pro identifikaci selhání společnosti (bankrotu) pomocí umělých neuronových sítí s alespoň jednou vrstvou dlouhodobé krátkodobé paměti (LSTM - long short-term memory). Model bankrotu byl vytvořen pomocí hlubokého učení, pro které byla pro konstrukci neuronových sítí použita alespoň jedna vrstva LSTM. Pro účely tohoto příspěvku byl použit software Wolfram Mathematica 13.

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Citovat

VOCHOZKA, Marek, Jaromír VRBKA and Petr ŠULEŘ. Bankruptcy or success? The effective prediction of a company's financial development using LSTM. Sustainability. Basel, Switzerland: MDPI, 2020, vol. 12, No 18, p. nestránkováno, 18 pp. ISSN 2071-1050. Available from: https://dx.doi.org/10.3390/su12187529.

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   keywords = {bankruptcy models; company; long short-term memory (LSTM); neural networks (NN); prediction; success},
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N2  - The objective of this contribution is to create a methodology for the identification of a company failure (bankruptcy) using artificial neural networks with at least one long short-term memory (LSTM) layer. A bankruptcy model was created using deep learning, for which at least one layer of LSTM was used for the construction of the NN. For the purposes of this contribution, Wolfram's Mathematica 13.
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VOCHOZKA, Marek, Jaromír VRBKA and Petr ŠULEŘ. Bankruptcy or success? The effective prediction of a company's financial development using LSTM. \textit{Sustainability}. Basel, Switzerland: MDPI, 2020, vol.~12, No~18, p.~nestránkováno, 18 pp. ISSN~2071-1050. Available from: https://dx.doi.org/10.3390/su12187529.

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