Research On The Interconnectedness Of China’s Financial Institutions Based On Quantile Network

During the process of financial globalization,financial institutions such as banks,securities companies,and insurers penetrated their business issues with each other and exhibited significant network characteristics.On the one hand,this high degree of network interconnectedness has improved the efficiency of financial asset allocation,but on the other hand,it has also led to the financial risk contagion more widespread,making it possible for a local crisis in one sector to turn into a regional or even global financial crisis.Therefore,measuring network connectedness accurately plays an important role in preventing and resolving systemic financial risks and maintaining the safety of the financial system.We construct quantile financial networks using the daily returns of 30 financial institutions listed on the A-share market,and also use the partial cross-quantilogram and quantile granger causality method to construct an undirected network with weight and a directed network without weight respectively.At the partial cross-quantilogram network level,firstly,construct a network based on daily returns and use the planar maximum filtering method to filter it;secondly,select institution-level and network-level indicators to measure network connectedness and identify systemically important financial institutions,finally,construct dynamic quantile networks using a rolling window approach and measure the trend of connectedness over time.At quantile granger causality network,firstly,construct directed network based on daily returns;secondly,use PCA method to construct institution-level indicators;finally,the static and dynamic analysis of the network connectedness is carried out at the system-level and the institutional-level respectively.We find that financial institutions are strongly interconnected at left and right tails rather than at the median.The network connectedness rises rapidly during the period of major risk events.The systemic importance of the three sectors significantly differs in different market conditions,with the securities industry playing an important risk spillover role during bearish and banks,particularly state-owned commercial banks,acting as important risk spillovers during bullish.The quantile network model constructed in this paper provides a new perspective for studying network connectedness.Our findings can effectively reveal the evolution of network connectedness,which has important practical implications for managing financial market risks and optimising investment portfolios.