Analysis Of Industry Risk Spillover Effect Based On Copula Entropy

Since the crisis,issues related to systemic risk have received wide attention from national regulators.Considering the definitions and studies of systemic risk in recent years,we can conclude that systemic financial risk has the characteristics of integrity,negative externality,infectivity and spillover effect.Whether it was the early Basel ?and Basel ?,or the Basel ? after the financial crisis,it focused on monitoring the individual risks of financial institutions.However,the frequent occurrence of financial crises confirms that monitoring individual risks alone can not prevent the accumulation and burst of systemic risks.In recent years,Sino-US trade friction has been escalating.At present,2019-nCoV has gradually evolved into a major global public health event.Recently,the global economic growth rate has slowed down,and the economic policy uncertainty of most countries has increased.All of these factors will lead to greater volatility in Chinese stock market.With the gradual openness of the stock market in China,the degree of economic and financial integration has been gradually promoted,and the high correlation between various industries within the market has further increased the possibility of systemic crisis.Accurate measurement of cross-industry risk spillover effect is very important to prevent and resolve systemic risk.This paper mainly solves two problems:First,many people study the risk spillover relationship between industries based on two-dimensional perspective,but the two-dimensional research idea ignores the superposition effect caused by multi-point risk crossover.Second,under different model frameworks,the influence of different extreme event shocks on the risk spillover relationship of the industry is not consistent,and lacks a unified research framework to study the industry's own risk and the risk linkage between industries.Based on the daily logarithmic returns of 11 industries in China's stock market from July 3,2006 to July 3,20 20,we decompose multi-variable joint entropy into the independent entropy and Copula entropy.Firstly,we study the dynamic evolution characteristics of individual risk and cross-industry risk spillover characteristics in 11 industries in China during the whole sample period.Secondly,we analyze the characteristics of industry risk in three special periods,such as the 2008 financial crisis period,the 2013 money shortage period and the 2015 stock disaster period.Finally,we analyze the evolution characteristics of industry risk network topology.The results show that:firstly,based on the analysis results of the whole sample period,the independent entropy sequence of each industry index and the 11-element Copula entropy sequence have obvious procyclicality and periodic characteristics,and the change of the 11-element Copula entropy sequence lags behind the cumulative independent entropy in most periods;Secondly,compared with the financial crisis in 2008,the market was more infectious and destructive in the period of stock disaster in 2015,the market reacted more quickly to the impact,the cumulative independent entropy had a strong negative correlation with the 11-element Copula entropy,and the 11-element Copula entropy change lagged behind the joint entropy value obviously.The overall impact of the money shortage event on the stock market in China in 2013 was relatively small;Thirdly,the risks involved in high-risk industries,such as real estate and finance,were largely released after the 2008 financial crisis,the 2013 money shortage and the 2015 stock disaster,but the level of correlation between the financial industry and the real estate industry has been maintained at a high level,and the telecommunications service industry and the information technology industry have gradually evolved into high-risk industries;Fourthly,the level of correlation between materials,industry,information technology,optional consumption and public utilities has remained at a high level throughout the sample period,while the risk level of the information technology industry has basically ranked the top three;Fifthly,recently,there is a strong correlation level in 11 industries in China,the risk level of information technology,telecommunication service and daily consumption industry is high,and the network structure with energy,materials,industry,optional consumption,information technology and public utilities as the main strong correlation nodes has been formed.