Predicting bank insolvencies using machine learning techniques
Year of publication: |
2020
|
---|---|
Authors: | Petropoulos, Anastasios ; Siakoulis, Vasilis ; Stavroulakis, Evangelos ; Vlachogiannakis, Nikolaos E. |
Published in: |
International journal of forecasting. - Amsterdam [u.a.] : Elsevier, ISSN 0169-2070, ZDB-ID 283943-X. - Vol. 36.2020, 3, p. 1092-1113
|
Subject: | Bank's insolvencies | Forecasting | Random Forests | Support Vector Machines | Neural Networks | Conditional inference trees | Prognoseverfahren | Forecasting model | Neuronale Netze | Neural networks | Bankinsolvenz | Bank failure | Insolvenz | Insolvency | Mustererkennung | Pattern recognition | Künstliche Intelligenz | Artificial intelligence |
-
Towards an early warning system for sovereign defaults leveraging on machine learning methodologies
Petropoulos, Anastasios, (2022)
-
Forecasting sovereign risk in the euro area via machine learning
Belly, Guillaume, (2023)
-
Le, Hong Hanh, (2018)
- More ...
-
Petropoulos, Anastasios, (2023)
-
Towards an early warning system for sovereign defaults leveraging on machine learning methodologies
Petropoulos, Anastasios, (2022)
-
Forecasting private sector bank deposits in Greece : determinants for trend and shock effects
Petropoulos, Anastasios, (2018)
- More ...