Research On Dependence Of Industry Volatility In Stock Market

With the deepening of global economic integration,the linkage between financial markets is getting stronger and stronger,the relationship between them is more complicated,and the synergy between markets is getting stronger.The financial crisis that erupted in 2008 has had a profound impact on the global economy.On the one hand,it reflects the need to study the systematic risks and the spread of the crisis in the financial market.It also reflects the current lack of reasonable quantification to effectively monitor risks.And effective measurement methods;and the European debt crisis a few years later once again warned us to pay attention to financial risk research.In our country,the economic system is constantly improving and reforming,and the interdependence and mutual influence among the various sectors in the market are becoming more and more close.Therefore,the research on the risk dependence between the various sectors in the market has gradually entered the risk researcher’s sight.In the market,the rise or fall of a certain sector is often accompanied by the rise or fall of other related financial sectors,and there is likely to be a correlation between the various assets contained in the portfolio of investors,which is highly risky.Conduction,which in turn affects the accuracy of the combined risk metric.For this reason,market risks are increasingly concerned by investors,and quantifying risks has gradually become the focus of financial risk management.With the continuous development of risk management theory,the Copula model is a statistical model that can estimate the structure of multiple variable dependencies.This study attempts to combine the GJR-GARCH model,the GPD distribution of extremum theory with the Vine-Copula function,using the daily logarithmic rate of return data to study and explore the risk dependence between the real estate industry,the building materials industry,the transportation industry and the banking industry.In this paper,we first use the GJR-GARCH model to filter the data.Considering the thick tail of the financial sequence,we construct the tail sequence with the GPD distribution,and finally use the C-Vine-Copula model to derive the vine structure between the four industries.The leading industries were identified and the corresponding VaR values were calculated,and the VaR values were verified by retrospective testing,which effectively described the high-dimensional risks of the industry.This paper provides a new technical method for our future risk management measurement research.It also provides more accurate theoretical support for government regulatory authorities,major financial institutions and investors in risk control,and further maintains the bottom line of financial risks.