Research On The Measurement And Application Of Real-time Financial Uncertainty In China

With the global financial crisis that broke out in 2008,researchers from central banks and government agencies in various countries have paid more attention to the correlation between the performance of financial system fluctuations and the macro economy.Especially with the outbreak of the new crown epidemic,the economic and financial uncertainties of various countries have reached historical highs,and may remain high in the short term.To this end,many scholars have conducted a lot of theoretical and empirical analysis around the economic uncertainty index,and a series of economic uncertainty indexes have been compiled one after another.This is useful for monitoring changes in my country’s overall economic situation and making early warnings to prevent crises.Play an important role.However,there are still few studies on the uncertainty index of the financial market in my country.In particular,the uncertainty index constructed by scholars is often at the same frequency,and there is a lack of real-time uncertainty index design,measurement and application research.Therefore,based on the current research status in our country,this article has made a mixed improvement to the financial uncertainty measurement method,and enriched the theoretical system of my country’s financial uncertainty index.This paper adopts the big data theory proposed by Jurado et al.(2015)[7],and selects 280 economic and financial variables composed of seasonal,monthly,and daily mixed data samples from January 1,2002 to September 30,2020.,Innovatively modified the construction of China’s financial uncertainty index through the method of mixing big data,and improved the BD-SV-FM model to the BD-MF-SV-FM model,and obtained China’s first The real-time financial uncertainty index,which has the advantage of real-time,can more accurately measure China’s financial uncertainty.This paper also compares the conduction between the financial uncertainty index and the stock market volatility,and the systemic risk indicators of financial institution constituted by the value at risk(CoVaR)method.The results show that:(1)China’s real-time financial The certainty index is reasonable and effective,and has a better role in identifying financial shock events.(2)After the lagging volatility is effectively controlled,the financial uncertainty index constructed through the mixed data model has a significant predictive effect on the volatility of the stock market and is a more essential source of volatility.(3)When financial uncertainty increases,the systemic risks of financial institutions will also increase significantly.The government can effectively identify and prevent systemic risks through the uncertainty index.In addition,the index constructed in this article has the advantage of real-time update and can be used as a risk warning indicator for the central bank.