Dynamic Forecasting for Systemic Risk in China's Commercial Banking Industry Based on Sequence Decomposition and Reconstruction

doi:10.1109/ACCESS.2023.3335609

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	Dynamic Forecasting for Systemic Risk in China's Commercial Banking Industry Based on Sequence Decomposition and Reconstruction
	Li, Zhengyong 1; Fu, Deyin1,2 ; Li, Haiting 3
	2023
发表期刊	IEEE ACCESS
卷号	11 页码:132068-132077
摘要	The Pressure Index of commercial banks is an effective measure of the systemic risk in the sector. This helps decision makers and market participants assess the potential levels of stress that commercial banks may face when confronted with impending risks. This study proposes a method for forecasting future trends in a Pressure Index for systemic risk prediction. The banking stress index is specifically constructed through an extreme value approach, followed by a non-stationary time series decomposition using variational mode decomposition (VMD). The number of decompositions was determined using the fuzzy entropy (FE) rule. These models were then used to construct autoregressive integrated moving average (ARIMA), artificial neural network (ANN), backpropagation neural network (BP), recurrent neural network (RNN), and long short-term memory (LSTM) models for independent prediction. The empirical results demonstrate the significant advantages of the VMD technique for forecasting non-linear and non-stationary complex time series. These findings highlight the substantial benefits of using VMD in forecasting intricate temporal patterns, especially in cases where traditional methods may face challenges in effectively capturing underlying dynamics. The VMD-ARIMA model showed superior prediction accuracy compared with the other models. Our study aims to model and forecast the data of the banking stress index, which is of utmost importance for the central bank in formulating macroeconomic policies and for commercial banks in managing credit risk.
关键词	Biological system modeling Banking Predictive models Indexes Time series analysis Data models Risk management Forecasting China's commercial banking industry systemic risk forecasting variational mode decomposition
DOI	10.1109/ACCESS.2023.3335609
收录类别	SCIE ; EI
ISSN	2169-3536
语种	英语
WOS研究方向	Computer Science ; Engineering ; Telecommunications
WOS类目	Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS记录号	WOS:001119339300001
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
EI入藏号	20234815122855
EI主题词	Variational mode decomposition
EI分类号	461.9 Biology ; 716.1 Information Theory and Signal Processing ; 802.2 Chemical Reactions ; 912.2 Management ; 914.1 Accidents and Accident Prevention ; 922.2 Mathematical Statistics
原始文献类型	Article
EISSN	2169-3536
引用统计	被引频次：1[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.lzufe.edu.cn/handle/39EH0E1M/35475
专题	校领导
通讯作者	Li, Zhengyong
作者单位	1.Lanzhou Univ Finance & Econ, Sch Stat & Data Sci, Lanzhou 730020, Peoples R China; 2.China Univ Lab Relat, Sch Labor & Econ, Beijing 10048, Peoples R China; 3.Lanzhou Univ Finance & Econ, Off Admiss & Employment, Lanzhou 730020, Peoples R China
第一作者单位	兰州财经大学
通讯作者单位	兰州财经大学
推荐引用方式 GB/T 7714	Li, Zhengyong,Fu, Deyin,Li, Haiting. Dynamic Forecasting for Systemic Risk in China's Commercial Banking Industry Based on Sequence Decomposition and Reconstruction[J]. IEEE ACCESS,2023,11:132068-132077.
APA	Li, Zhengyong,Fu, Deyin,&Li, Haiting.(2023).Dynamic Forecasting for Systemic Risk in China's Commercial Banking Industry Based on Sequence Decomposition and Reconstruction.IEEE ACCESS,11,132068-132077.
MLA	Li, Zhengyong,et al."Dynamic Forecasting for Systemic Risk in China's Commercial Banking Industry Based on Sequence Decomposition and Reconstruction".IEEE ACCESS 11(2023):132068-132077.