Researcresearch On Macro-Prudential Supervision In China From The Angle Of Systemically Important Financial Institutions (SIFIs) Identification

The financial crisis in2008has prompted the globalsupervisiontheoryto focus on not only guard against market risk ofindividual financial institutionsbut systemic risk, focus on not only ‘toobig to fail’, but ‘too associated to fail’ to the same importance.Especially,post-crisis era has seenheightened uncertainty,posing a huge threat onglobally and nationally financial stability.A macro-prudential supervisionsystem,designed to prevent systemic risk and maintainstability offinancial institution, becomes the core of the new regulatoryphilosophy.Meanwhile, measuring systemic risk andidentifyingsystemically important institutions(SIFIs)are the basic premise and firststep of the macro-prudential supervision.In view of this, having fullylearning the theory and practice of domestic and international experience,through a systematic and multi-angle measurement of financial systemicrisk, this paper identifies systemically important institutions(SIFIs), andanalysizes the difference between the measurement results and impactfactors,which contributes to provide constructive suggestionsforimproving macro-prudential supervision system in China.This paper chooses16commercial listed banksfrom Shanghai andShenzhen stock exchange center,andthe sample interval is from year2007to year2013. Firstly, for the first time we integratedly use market-data-based CoVaR methodwith quantile regression,andFinancial-data-based index system method, and furthersubdividedquantile regression to1%and5%quantileregression tomeasure systemic risk, and indentify SIFIs, and analysize the variance ofresults, explore the practicality of two types of three methods. Secondly, the sample interval is divided into financial crisis and non-crisis periodinterval, and results are discussed by year during non-crisis period, inorder to observe the evolution of systemic risk characteristics to find thekey nodes of systemic risk. Thirdly, mixed regression model is used toexplore the common factors that influence systemic risk under differentcalculation methods. Finally,the reliability of main conclusions is verifiedby three robust tests--time span transformation, agency variables change,and measurement transformation.Results show that:(1) The systemic risk rank issusceptible tocalculation method, but obeysome certain regularity.Under1%quantileregression method and indicator method, the SIFIs ranking followsstate-owned commercial banks> national joint-stock commercial banks>local joint-stock commercial banks; while under5%quantileregression,onthe whole the ranking followsfollow-owned business Bank>joint-stock commercial banks.(2) By subdividing periods, the evolutioncharacteristics of the systemic risk are as follows. a) the risk spillovereffectof joint-stock commercial banks is more easily affected by theestimation methods, and the estimation under5%quantile regression ishigher compared with1%; b) the risk spillover effectof state-ownedbanks ismore significant than joint-stock commercial banks during boththe financial crisis or the non-crisis period; c) Banks in China have someperiod features in contribution of financially systemic risk, i.e., systemicrisk value and risk spillover effect during the crisis is significantlylarger.(3) The factors of contribution of systemic risk is not significantlysubject to measurement of systemic risk. Banks with bigger assetsize,higher non-performing loan ratio, and higher leverage ratio canhavegreater risk of spillover and contagion effectonce trapped in crisisitself;and macroeconomic fluctuation risk also has a significant impact onthe contagion effect; data also show that the profitability of the big banksare not absolutely positive with the risk contribution.(4) The role of theregulatory measures currently entirely based on a single individual bankrisk is limited, and CoVaR--risk measurement techniqueis morecomprehensive than the VaRin terms of capturing risk, and VaR approach could lead to banks’overflow level of systemic risk underestimated.Recommendations specifically consistent withabove results are asfollows. Firstly, strengthening the supervision of SIFIs, especially thesupervision of state-owned commercial banks in China, and refining thestandards, and controlling the size and complexity of the business ofSIFIs is necessary. Secondly, a strict ‘firewall’ system is suggested to beestablished, to preventspillover risks of cross-sector and cross-borderbanks. Thirdly, we should establish the counter-cyclical capital regulation,by implementingdynamic capital regulation, establishing loan lossprovisioning system, and using full-cycle credit rating methods tosuppress the huge costs of financial instability. Finally, the ChinesePeople’s Bank should play the functions of of regulatory coordinationsothat macro-prudential supervision,monetary policy, and fiscal policy cancomplement and cooperate with each other in order to maintain financialand macroeconomicto runsmoothly.