| In 2008,the "subprime crisis" that started in the United States evolved into a global financial crisis,indicating that once risks are locally concentrated and broke out,they tend to spread rapidly in the financial system,and then spread to the entire macro economy,forming a "domino effect" and eventually leading to economic recession.With the increase of financial services to the real economy in China,the two are more closely linked,and the bad development of the real economy industry is likely to lead to the accelerated accumulation of risks in various industries,and cause the inevitable risk impact on the financial industry.Therefore,the risk spillover effects between finance and entity industry is worth paying attention to.In addition,under the background of Sino-US trade friction,the world's two largest economies will play continuous game on disputes,and the characteristics of its uncertainty will continue to affect the economic and trade exchanges between China and the United States,it will also bring a lot of uncertainty to China's financial industry and the real economy industry,which may further become a potential threat to China's economic and financial stability,so it has become an important issue of high concern to all aspects of the society.This paper takes the daily closing prices of twelve industry indexes in banking,banking sector,non-bank financial sector,communications,agriculture,forestry,animal husbandry and fishery,medicine and biology,electronics,transportation,textiles and clothing,machinery and equipment,chemicals,light industry manufacturing,and non-ferrous metals as research objects.Taking the Sino-US trade friction as the time node,the sample is divided into two intervals,and the time-varying Copula-EVTCoVaR model is used to compare and analyze the risk spillover effects within the financial industry,between the financial industry and real economy industry.In order to reduce the impact of typical factual characteristics of financial time series on the empirical results,firstly,the AR(1)-GARCH(1,1)model under skew-t distribution was used to filter the yield data of financial industry and real industry after logarithmic firstorder difference processing,so as to obtain the standard residual sequence,and then the marginal distribution is constructed pieceously with EVT model.In order to better characterize the dynamic correlation between the financial industry,the financial industry and the real economy industry,this paper uses the marginal distribution to fit three common static Copulas model and its corresponding time-varying Copulas,mainly including Normal Copula,Clayton Copula and t copula.Then,according to AIC principle,the best fitting time-varying Copula model was selected and incorporated into CoVaR to quantify the change trend of risk spillover effects inside of financial industry,between the financial industry and real economy industry.Quantitative indicators mainly use(35)CoVaR and %(35)CoVaR.The research conclusions obtained through empirical analysis in this paper are as follows:(1)The AR(1)-GARCH(1,1)-EVT-skew-t model better depict the thick tail,autocorrelation and other typical factual characteristics of financial industry and real economy industry stock index yield.The marginal distribution is able to match independent identically distributed condition,which is suitable for further establishing a time-varying Copula model.According to the EVT model parameters,the lower-tail's distribution of most industries does have a thick tail,which becomes more apparent during the period of Sino-US trade friction.By comparison,it is found that the timevarying t Copula has the best fitting effect for the dependency relationship between the inside of financial industry,the financial industry and real economy industry,which also reflects the complex tail correlation between the two.Therefore,it is reasonable for this paper to build a time-varying Copula-EVT-CoVaR model to quantitatively analyze the extreme risk spillover effect S between the financial industry and the real industry.(2)According to the lower-tail correlation coefficient,it can be found that during the period of Sino-US trade friction,there is no significant change in the positive correlation between the banking sector and the non-bank financial sector,while the lower-tail correlation between real economy industry and the financial industry has been strengthened and some of the volatility has increased,but this kind of change has certain difference.(3)As for the duration of Sino-US trade friction,the Va R of the financial industry and real economy industry has increased,which indicated that this event increased the probability of risks in the financial industry and real economy industry.In addition,the Va R of non-bank financial sector is still greater than that of banking sector and the changes are more obvious.(4)The trade friction between China and the United States has no obvious effect on the risk spillover effects within the financial industry,while the risk spillover effects of the banking sector to other industries is much stronger than the reverse spillover,showing asymmetry,indicating that the banking sector is the main source of risk contagion.Meanwhile,during the period of Sino-US trade friction,risk spillover effects from other industries to the banking sector were small and very stable,which reflected the stronger ability of the banking sector to withstand the impact of external risks,and it also reflected that the banking sector had a good effect in preventing and defusing risks during the period of Sino-US trade friction.(5)As for the duration of Sino-US trade friction,the risk spillover effects of entity industry on the financial industry is different,and this risk spillover effects is dynamic,which will gradually weaken with the introduction of relevant regulatory policies and the easing of Sino-US trade friction.Among them,the risk spillovers of agriculture,forestry,animal husbandry and fishery,transportation,machinery and equipment,electronics,communications,textiles,clothing and chemical industries to the financial industry have changed significantly,while the risk spillovers of the banking sector and non-bank financial sector to the transportation,machinery and equipment,electronics,communications,textile and clothing,and chemical industry are relatively strong,indicating that the Sino-US trade friction made these real economy industries more sensitive to the changes in the financial and economic environment.Finally,based on the empirical conclusions and the fact that the current sino-us trade relationship is unpredictable,it has provided corresponding risk management policy recommendations for China's real economy industry,financial industry and financial regulatory agencies. |
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