DocumentCode
3570514
Title
Early warning model of crisis in Chinese commercial banks based on gray relational analysis with double standard
Author
Sun Xiufeng ; Yu Xixuan
Author_Institution
Dept. of Bus. Manage., Dalian Univ. of Technol., Dalian, China
fYear
2014
Firstpage
210
Lastpage
216
Abstract
China lacks examples of bank crises and reference standards for classifying such crises. This study addresses these problem by designing an ideal bank crisis based on four types of early warning indices of endogenous risk, capital and asset safety, profitability, and liquidity. An early warning model of commercial bank crises is created based on a novel modified Gray relational analysis. This model is capable of classifying banks into three levels of crisis and of evaluating the final crisis value. This study also performs an empirical analysis. Results demonstrate that an early warning model of commercial bank crises classifies and orders the sample data based on forecasting criticality. The model was tested during the risky events in China´s commercial banks in mid-2013. The 62 sample banks were all preferably safe in 2012. The risk control of the city commercial banks was better than that of large and joint-stock commercial banks. However, the possibility of crisis growth in China´s commercial banks remains.
Keywords
banking; grey systems; investment; risk management; Chinese commercial banks; bank crisis classification; capital and asset safety index; crisis early warning model; empirical analysis; endogenous risk index; forecasting criticality; gray relational analysis; liquidity index; profitability index; risk control; Banking; Computational modeling; Data mining; Data models; Mathematical model; Risk management; Standards; commercial bank; data mining; early warning of crisis; ideal commercial banks; novel modified Gray relational analysis; risk management;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Science and Systems Engineering (CCSSE), 2014 IEEE International Conference on
Print_ISBN
978-1-4799-6396-6
Type
conf
DOI
10.1109/CCSSE.2014.7224539
Filename
7224539
Link To Document