Search Results - subject:"Bank failure prediction"

Survival of Russian banks: How efficient are the control measures?

Barajas, Angel; Krakovich, Victor; López Iturriaga, … - In: European Journal of Management and Business Economics … 32 (2023) 3, pp. 320-341

Purpose - In this paper, the authors study the failure of Russian banks between 2012 and 2019. Design/methodology/approach The authors analyze the entire population of Russian banks and combine a logit model with the survival analysis. Findings In addition to the usual determinants, the authors...

Persistent link: https://www.econbiz.de/10015454515

Survival of Russian banks : how efficient are the control measures?

Barajas, Angel; Krakovich, Victor; López Iturriaga, … - In: European journal of management and business economics : … 32 (2023) 3, pp. 320-341

Purpose In this paper, the authors study the failure of Russian banks between 2012 and 2019. Design/methodology/approach The authors analyze the entire population of Russian banks and combine a logit model with the survival analysis. Findings In addition to the usual determinants, the authors...

Persistent link: https://www.econbiz.de/10014318831

ELPR : a new measure of capital adequacy for commercial banks

Lee, Charles M. C.; Wang, Yanruo; Zhong, Qinlin - In: The accounting review : a publication of the American … 99 (2024) 1, pp. 337-365

Persistent link: https://www.econbiz.de/10014475568

Predicting bank failures: A synthesis of literature and directions for future research

Liu, Li Xian; Liu, Shuangzhe; Sathye, Milind - In: Journal of Risk and Financial Management 14 (2021) 10, pp. 1-24

-learning and statistical techniques used in the literature on bank failure prediction. The study finds that though considerable …

Persistent link: https://www.econbiz.de/10013201158

Predicting bank failures : a synthesis of literature and directions for future research

Liu, Li Xian; Liu, Shuangzhe; Sathye, Milind - In: Journal of risk and financial management : JRFM 14 (2021) 10, pp. 1-24

-learning and statistical techniques used in the literature on bank failure prediction. The study finds that though considerable …

Persistent link: https://www.econbiz.de/10012745256

Using boosting algorithms to predict bank failure : an untold story

Pham, Xuan T. T.; Ho, Tin H. - In: International review of economics & finance : IREF 76 (2021), pp. 40-54

Persistent link: https://www.econbiz.de/10013175742

An ordinal classification framework for bank failure prediction : methodology and empirical evidence for US banks

Manthoulis, Georgios; Doumpos, Michalis; Zopounidis, … - In: European journal of operational research : EJOR 282 (2020) 2, pp. 786-801

Persistent link: https://www.econbiz.de/10012157978

Anticipating bank distress in the Eurozone : an Extreme Gradient Boosting approach

Climent Diranzo, Francisco J.; Momparler, Alexandre; … - In: Journal of business research : JBR 101 (2019), pp. 885-896

Persistent link: https://www.econbiz.de/10012103653

Bank failure prediction in relation to the business life cycle

Wang, Yishu; Yang, Jing; Liu, Zhenjia - In: Modern economy 10 (2019) 3, pp. 757-777

Persistent link: https://www.econbiz.de/10012019721

Predicting failure in the US banking sector : an extreme gradient boosting approach

Carmona, Pedro; Climent, Francisco; Momparler, Alexandre - In: International review of economics & finance : IREF 61 (2019), pp. 304-323

Persistent link: https://www.econbiz.de/10012205428