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Research On The Construction And Application Of China's Real-time Time-varying Financial Condition Index Based On Mixed-frequency Loss Function

Posted on:2022-02-23Degree:MasterType:Thesis
Country:ChinaCandidate:J J ChenFull Text:PDF
GTID:2480306539988869Subject:Industrial Economics
Abstract/Summary:PDF Full Text Request
Under the situation of the deep integration of domestic and foreign economies,China has relied on the “Belt and Road” and other comprehensive open economic development policies to make economic development more abundant.At the same time,sources of financial risks have become more extensive,and financial stability will become more difficult to guarantee.In the case of monetary policy lagging,it is necessary to emphasize the forward-looking and targeted regulation of monetary policy.Therefore,this paper constructs a dual-objective loss function,and compiles China's Real-Time Time-varying Financial Condition Index(RTVFCI)based on this.The first chapter of this article introduces the current domestic and international economic environment,analyzes and summarizes the current research results of FCI construction and application.The second chapter introduces the relevant theoretical background of the financial condition index.Chapter 3 introduces the construction and calculation process of the mixed-frequency mixing innovation time-varying coefficient random variance vector autoregressive model(MF-MI-TVP-SV-VAR),and introduces the construction process of the mixed-frequency loss function model.The fourth chapter measures China's Real-Time Time-varying Financial Condition Index.First of all,it is the preliminary selection and processing of data.Secondly,it extracts the structural common factors of money supply,credit,interest rate,exchange rate,stock price and housing price according to China's economic development.At last,adding mixed-frequency loss function MLF,a total of 7 columns of data are put into the model to calculate and compile the China's RTVFCI and analyze the empirical results of the calculation..The fifth chapter analyzes the relationship between China's RTVFCI and CPI and GDP from correlation,leadership,causality and predictability,and compares it with China's Delayed-Time Time-varying Financial Condition Index(DTFCI).Chapter 6 is the further research and expansion of the practical application of RTVFCI in China,reflecting its actual value.The seventh chapter is a comprehensive summary of the full text and gives relevant policy recommendations.The empirical results show that: First,China's Mixed-frequency Loss Function(MLF)is a reasonable indicator that can comprehensively reflect the ultimate goal of China's monetary policy.Second,China's RTVFCI empirically compiled based on the MF-MI-TVP-SV-VAR model can cover more financial information and is more compatible with China's financial situation.Third,China's RTVFCI is superior to DTFCI in terms of relevance,leadership,causality,and predictability,indicating that China's RTVFCI is reasonable and effective.Fourth,China's RTVFCI can be used as a tool to analyze the uncertainty of China's monetary policy,and it is also an effective indicator for predicting China's systemic financial risks.The main innovations of this paper are as follows: First,newly constructed mixed-frequency and mixing innovative time-varying coefficient random variance vector autoregressive model(MF-MI-TVP-SV-VAR),which has the characteristics of mixing,flexibility,and time-varying;Second,a newly compiled China Real-Time Time-Varying Financial Condition Index(RTVFCI).Taking the mixed-frequency loss function(MLF)as the objective function,China's Real-Time Time-Varying Financial Condition Index estimated from the monthly and daily mixing sample data is constructed.With the improvement of financial markets and the increase of factors affecting monetary policy,this article may have the insufficiency of incomplete coverage of monetary policy influence paths.
Keywords/Search Tags:financial condition index, mixed-frequency loss function(MLF), real time and time variation, MF-MI-TVP-SV-VAR model, monetary policy
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