Construction Of Dynamic Financial Condition Index Based On Bayesian Method And Its Characteristics Analysis

Since the 2008 global financial crisis triggered by the US subprime mortgage crisis,the impact of the fluctuation of the financial system on the macroeconomy has become more and more important.It is more and more important to supervise and to be on alert for systemic financial risks.The Financial Condition Index(FCI)is a comprehensive index for measuring the overall changes of the financial market,which was an indicator and measurement index of monetary policy and macro-economy.Therefore,the construction of China’s FCI and its dynamic characteristics analysis are very important for China to prevent economic and financial risks.Based on existing research,this paper constructs two dynamic Financial Condition Indexes based on the Bayesian estimation method;and compares their fluctuation characteristics and weight differences,as well as the correlation between Financial Condition Index and China’s macroeconomy.The major contents of this paper are as follows:Firstly,the FCI is constructed by using the dynamic factor model,the aggregate demand reduction equation with the Bayesian estimation method,and TVP-VAR model,and the fluctuation characteristics and dynamic weight changes of the index are analyzed and compared.Secondly,through the Granger causality test,intertemporal correlation analysis,and regression equation,the effectiveness of the financial condition index is preliminarily tested and compared.Thirdly,the frequency domain analysis method is used to measure and compare the correlation between Financial Condition Index and the macro-economy.Finally,the volatility characteristics of the financial condition index itself are studied and the differences are compared through the Markov regime-switching model.The results of research show that: First,The overall trend of the Financial Condition Index constructed by different methods is not different,and it also has some commonalities in the description of the dynamic impact of financial variables on the financial market,but each has its emphasis.Second,both financial condition indexes can effectively predict inflation in the short term,but their prediction ability can be divided into strong and weak.Third,the Financial Condition Index and the macroeconomic main cycle are similar in length,but the two Financial Condition Indexes have different emphasis on the cyclical linkage relationship between output,macroeconomy,and inflation,while the gap between leading cycles is not large.Fourth,the financial condition index shows a certain periodic fluctuation.Each state of the financial condition index has a certain stability,but there are some differences in the judgment and identification of the expansion state of the financial market between the two Financial Condition Indexes.To sum up,the Financial Condition Index constructed by different methods focuses on the fluctuation characteristics,weight differences,and the correlation with China’s macro-economy,and its main application direction and scope should be determined according to the characteristic attributes of different financial condition indexes.It can be seen that the monetary authority should use a variety of methods to regularly prepare the Financial Condition Index and adjust the monetary policy according to the characteristics of different indexes.