The extraction of early warning features for predicting financial distress based on XGBoost model and shap framework
Year of publication: |
2021
|
---|---|
Authors: | Yang, He ; Li, Emma ; Cai, Yi Fang ; Li, Jiapei ; Yuan, George |
Published in: |
International journal of financial engineering. - New Jersey : World Scientific, ISSN 2424-7863, ZDB-ID 2832504-7. - Vol. 8.2021, 3, p. 1-24
|
Subject: | AUC and KS testing | early-warning feature | Financial distress | machine learning | SHAP framework | XGBoost | Prognoseverfahren | Forecasting model | Insolvenz | Insolvency | Frühwarnsystem | Early warning system | Betriebliche Liquidität | Corporate liquidity |
-
Ashraf, Sumaira, (2019)
-
Towards an early warning system for sovereign defaults leveraging on machine learning methodologies
Petropoulos, Anastasios, (2022)
-
Konstrukcja miernika szans na bankructwo firmy
Nehrebecka, Natalia, (2012)
- More ...
-
Li, Jiapei, (2024)
-
Capital formation and financial intermediation : the role of entrepreneur reputation formation
Li, Emma, (2019)
-
Venture capital certification and customer response : evidence from P2P lending platforms
Li, Emma, (2020)
- More ...