基于马尔科夫模型的我国金融系统性风险预警研究

Early warning of financial systemic risk in China:Based on Markov regime-switching model

为推动我国金融系统性风险预警研究,在分析金融系统性风险的传导路径、借鉴国际经验的基础上,综合考虑金融系统内外部因素,重构符合我国实际的金融系统性风险预警指标体系,并合成包含资产泡沫、货币危机、外汇市场和其他共四个金融压力指数的金融综合压力指数.选取2001年~2016年历史数据,采用马尔科夫区制转移模型与主成分分析法相结合,对我国金融系统性风险预警进行实证分析.结果表明,该方法有效识别了该时期高风险时间点;预测结果有效验证了我国2017年处于较低的金融系统性风险状态.揭示了房市泡沫调控、银行信贷管理、实体经济管理体系不完善、消费投资需求疲软等问题是引发我国金融系统性危机的隐患.

Considering the transmission mechanism of financial systemic risks and international experiences,as well as the internal and external factors of the financial system,this study reconstructs an early-warning system of financial systemic risk for China.Then,a financial composite pressure index,including asset bubbles,currency crisis,foreign exchange market and others,is built.Finally,using historical data from 2001 to 2016,the paper empirically analyzes the early warning of financial systemic risk in China by combining Markov regime-switching model and principal component analysis in order to promote the research of China’s early warning of financial systemic risk.The results indicate that the proposed system could effectively identify the high-risk time points in this period and verifies that China is in a state of low financial systemic risk in 2017.In addition,this study reveals that factors such as the housing market regulation,bank credit management,imperfect real economy management system and weak demand for consumption investment are the latent dangers of China’s financial systemic crisis.