Search Results - subject:"Random Forest algorithms"

An approach for variable selection and prediction model for estimating the Risk-Based Capital (RBC) based on machine learning algorithms

Park, Jaewon; Shin, Minsoo - In: Risks 10 (2022) 1, pp. 1-20

techniques: Random Forest algorithms and the Bayesian Regulatory Neural Network (BRNN). The combination of Random Forest … algorithms and BRNN predicts the next period's RBC ratio better than the conventional statistical method, which uses ordinary …

Persistent link: https://www.econbiz.de/10013200904

An approach for variable selection and prediction model for estimating the Risk-Based Capital (RBC) based on machine learning algorithms

Park, Jaewon; Shin, Minsoo - In: Risks : open access journal 10 (2022) 1, pp. 1-20

Persistent link: https://www.econbiz.de/10012805414

Estimating the BIS capital adequacy ratio for Korean banks using machine learning: Predicting by variable selection using random forest algorithms

Park, Jaewon; Shin, Minsoo; Heo, Wookjae - In: Risks 9 (2021) 2, pp. 1-19

The purpose of this study is to find the most important variables that represent the future projections of the Bank of International Settlements' (BIS) capital adequacy ratio, which is the index of financial soundness in a bank as a comprehensive and important measure of capital adequacy. This...

Persistent link: https://www.econbiz.de/10013200701

Estimating the BIS capital adequacy ratio for Korean banks using machine learning : predicting by variable selection using random forest algorithms

Park, Jaewon; Shin, Minsoo; Heo, Wookjae - In: Risks : open access journal 9 (2021) 2/32, pp. 1-19

Persistent link: https://www.econbiz.de/10012426967