Author(s)

Jizhou Li^1,2, Yang Yang^2,3*, Liang Zhou⁴

¹International Business College, Dongbei University of Finance and Economics, Dalian, China.
²Hunan Key Laboratory of Macroeconomic Big Data Mining and Its Application, Changsha, China.
³School of Business, Hunan Normal University, Changsha, China.
⁴School of Finance, Hunan University of Finance and Economics, Changsha, China.

As China’s participation in the global market intensifies, the systemic risk arising from its expansive and interconnected economy becomes increasingly significant worldwide. The inherent complexity of systemic risk necessitates the integration of a wide array of information sources for its accurate assessment. In this context, our study utilizes the mixed-frequency dynamic factor model to develop a Systemic Risk Index (SRI) that effectively encapsulates. This model is adept at merging data indicators from varying frequencies, which is crucial for capturing the multifaceted nature of systemic risk. Moreover, the study further delves into the macroeconomic early warning capabilities of the SRI. Our findings demonstrate that the SRI is proficient in integrating and distilling information from diverse market dimensions, offering a more nuanced representation of China’s economic and financial risks. Moreover, the SRI exhibits a robust capacity for economic foresight, outpacing macroeconomic indicators by a minimum of 12 months.

Systemic Risk Index, Economic Warning, Mixed-Frequency Dynamic Factor Model

Li, J. , Yang, Y. and Zhou, L. (2024) Systemic Risk Measurement and Its Economic Early Warning Ability: Based on Mixed-Frequency Dynamic Factor Model. Theoretical Economics Letters, 14, 164-183. doi: 10.4236/tel.2024.141009.