中国金融风险识别与预测——基于Markov区制转移模型  

China Financial Risks Identification and Forecast——Based on Markov Regime Switching Model

作　　者：席文治 Xi Wenzhi(School of Statistics and Mathematics,Zhongnan University of Economics and Law,Wuhan 430073,China)

机构地区：[1]中南财经政法大学统计与数学学院,湖北武汉430073

出　　处：《中南财经政法大学研究生学报》2020年第4期21-30,共10页Journal of the Postgraduate of Zhongnan University of Economics and Law

基　　金：2019年中南财经政法大学研究生创新课题项目:数字普惠金融与消费扩张(项目编号:201911304)。部分研究成果。

摘　　要：新冠疫情对全球经济的发展造成了重大打击,中国金融市场同样会受到波及。使用金融压力指数法对中国2005年1月-2020年3月的金融风险进行测度,分别从国内金融市场、国际金融市场两方面,选取24项指标构建银行压力指数(BSI)、股票市场压力指数(SSI)、房地产压力指数(RESI)、宏观环境压力指数(MESI)、国际市场压力指数(ISI)五项分指数,综合得到中国系统性金融压力指数(FSI),再采用Markov区制转移模型识别金融风险时期,结果表明,中国金融子市场间具有关联性;中国系统性金融风险大多数时间处于低风险状态,低金融风险状态的持续期较长;2020年中国金融风险仍处于较低、可控水平。The COVID-19 pandemic has caused a huge shock to the development of the global economy,and the Chinese financial market will also be affected.Using the Financial Stress Index method to measure China s financial risks from January 2005 to March 2020,we selected 24 indicators to construct five sub-indexes from the domestic financial market and the international financial market:the Bank Pressure Index(BSI),the Stock Market Pressure Index(SSI),Real Estate Stress Index(RESI),Macro Environmental Stress Index(MESI)and International Market Stress Index(ISI).Finally comprehensively obtained China s systemic financial stress index(FSI),and then used Markov Regime Switching Model to identify periods of financial risks.The results show that there are correlations between China s financial sub-markets;China s systemic financial risks are in a low-risk state most of the time,and the duration of the low-financial risk state is longer;China s financial risks are still at a low and controllable level in 2020.

关 键 词：金融风险 金融压力指数 CRITIC赋权 MARKOV区制转移模型 ARMA模型 

分 类 号：F83[经济管理—金融学]