Research on Systemic Financial Risk Measurement Based on HMM and Text Mining: A Case of China Financial Market

被引:8
作者
Li, Zhanfeng [1 ]
Cai, Yanli [1 ]
Hu, Shulan [1 ]
机构
[1] Zhongnan Univ Econ & Law, Sch Math & Stat, Wuhan 430073, Peoples R China
关键词
Hidden Markov models; Indexes; Markov processes; Heuristic algorithms; Viterbi algorithm; Text mining; Stability criteria; Systemic financial risk; Baidu index; hidden Markov model; text mining;
D O I
10.1109/ACCESS.2021.3055967
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The paper considered the sensitivity of unstructured network data to external shocks in the financial system, based on HMM applied in the traditional financial indicator system to construct the new composite index. We integrated economic statistical structure data and internet information, to capture the internal correlation and external shocks to financial markets. There appeared to be some evidence that the new index was superior at measuring the systemic financial risk. In addition, according to the new composite index we constructed, China's systemic financial risk was at the medium high level. It is an important task to prevent the systemic financial risk and maintain the stability of macro-economy.
引用
收藏
页码:22171 / 22185
页数:15
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