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The application of graphic methods and the DEA in predicting the risk of bankruptcy

Štefko, Róbert; Horváthová, Jarmila; Mokrišová, … - In: Journal of risk and financial management : JRFM 14 (2021) 5, pp. 1-19

The paper deals with the issue of analyzing the financial failure of businesses. The aim was to select key performance indicators entering the DEA model. The research was carried out on a sample of 343 Slovak heat management companies. When addressing the research problem, we made use of...

Persistent link: https://www.econbiz.de/10012587360

Support vector machine methods and artificial neural networks used for the development of bankruptcy prediction models and their comparison

Horák, Jakub; Vrbka, Jaromir; Suler, Petr - In: Journal of risk and financial management : JRFM 13 (2020) 3/60, pp. 1-15

Bankruptcy prediction is always a topical issue. The activities of all business entities are directly or indirectly …

Persistent link: https://www.econbiz.de/10012302458

Equalizing seasonal time series using artificial neural networks in predicting the Euro-Yuan exchange rate

Vochozka, Marek; Horák, Jakub; Šuleř, Petr - In: Journal of risk and financial management : JRFM 12 (2019) 2/76, pp. 1-17

, while affecting it significantly in the short run. However, prediction of the exchange rate is very complicated. In this …

Persistent link: https://www.econbiz.de/10012022122

Countering cybercrime risks in financial institutions : forecasting information trends

Kuzior, Aleksandra; Brożek, Paulina; Kuzmenko, Olha; … - In: Journal of risk and financial management : JRFM 15 (2022) 12, pp. 1-22

This article aims to forecast the information trends related to the most popular cyberattacks, seen as the cyber-crimes' consequences reflecting on the Internet. The study database was formed based on online users' search engine requests regarding the terms "Cyberattacks on the computer systems...

Persistent link: https://www.econbiz.de/10014284116

The predictability of the exchange rate when combining machine learning and fundamental models

Zhang, Yuchen; Hamori, Shigeyuki - In: Journal of risk and financial management : JRFM 13 (2020) 3/48, pp. 1-16

prediction performance of random walk without drift. More specifically, this paper applies the random forest, support vector …

Persistent link: https://www.econbiz.de/10012174126