Research On Dependence And Risk Measurement Of Capital Market

China’s economic development has entered a new normal and has to simultaneously deal with the slowdown in economic growth,make difficult structural adjustments,and absorb the effects of previous economic stimulus policies.Under this situation,soft budget constraints hurt the economy worse,China’s financing is too dependent on indirect financing and debt,leverages soared.Financial sector uses loose monetary policy and complex trading structure to monetize monetary discipline slack while itself also entered a new developing period.Leverage,relevance and complexity are on the rise during this period.However,the current supervisory system cannot fully adapt to the rapid changes in the financial system.No forward-looking and targeted regulation system design has been made,which has led to the influx of monetary funds into the asset sector and higher asset prices.Since 2014,the real estate market in stocks,bonds,futures,and first-and second-tier cities has been hit by liquidity in turn,which in turn has caused asset price fluctuations.The CPC Central Committee highly pays close attention to the structural problems encountered in the area of economic and financial affairs.In the 19 th National Congress of the Financial Work held in 2017,the CPC Central Committee emphasized the following directions of development: deepen the reform of the financial system,enhance the real economy capacity of the financial services sector,increase the proportion of direct financing,promote the healthy development of a multi-level capital market,improve the dual-pillar regulatory framework for monetary policy and macro-prudential policies,deepen market-oriented interest rates and exchange rate reform,improve the financial regulatory system and maintain the bottom line where systemic financial risks do not occur.Clarifying the interactive dependence between multi-level capital markets and effectively measuring the risk under extreme conditions are the prerequisites for the healthy development of multi-level capital markets and the control of systemic financial risks.It is based on the above realistic reasons,based on the theory of asset price volatility and the related research results of domestic and foreign scholars on the capital market,this paper discusses the theoretical basis of asset price fluctuations,uses a variety of measurement methods,conducts a systematic and in-depth study on the dependence and extreme value of the returns on different stock indices in China’s stock market in the hope of making suggestions on the capital market construction.The first chapter of the dissertation gives an overview of the selected topic background,research significance,theoretical context and methodology,research framework,main innovations and dissertation structure.The article begins with the theoretical explanation by using game theory and general equilibrium analysis.Firstly,the state and time-varying features of the model are used to describe the state of the stock market as a whole.Then we focus on the market extreme case and analyze the characteristics of the structural relationship between the stock index under the extreme conditions from the dependent structure perspective,the influence of expected volatility on the extreme value distribution,the threshold uncertainty,information and tail dependence.Chapter 2 firstly points out the important role of the game in the price and its formation mechanism.The argument in game theory that the synthetic fallacy and the endogenous instability are equally applicable to price formation and price behavior.A typical price game can be described by the zero-sum game of the cross-section dimension and the Prisoners Dilemma game of the time dimension,inequalities in the design of the mechanism can significantly affect the game outcome.The structured game can be described by the general equilibrium model,and different equilibrium models correspond to the typical game mechanism design.Taking the perfect market as the benchmark model,the paper firstly introduces the mortgage,and points out that the mortgage enhances the balanced participation motivation of the price fluctuation.Then,by introducing the endogenous mortgage of belief,it is pointed out that only the non-parallel movement of belief structure will lead to the mortgage.Finally,by introducing the endogenous belief in parametric uncertainty,we point out that the decision-making of information gathering to alleviate the uncertainty of parameters is a complementary strategy and leads to multiple equilibrium when the uncertainty is high enough.In the above analysis,the final reduction of asset price volatility is the most fundamental purpose of the market: to collect and reflect the information owned by market participants to coordinate actions.The above analysis also implies the fact that: The interaction between asset prices may exhibit completely different characteristics under different market conditions.Changes in such characteristics are likely to be sudden,easy to fall into a cyclic,discontinuous,and more pronounced in extreme markets.The following is a measure of this fact from different sides.Chapter 3 begins with the use of regime and time-varying models to study the overall state of the stock market.We use RTV-VAR model and TVP-VAR model to analyze the regime and impulse response of typical stock indices return of China’s stock market in 2015.CSI 300 Granger causality is independent of others,the small and medium-sized board Index affects the CSI 300 through Growth Enterprises Market Board Index and CSI 500 Index,the former channel weakened and the latter reinforced in the volatility period,and the affects were offset.Considering the breakpoint probability and stochastic variance of the RTV-VAR model,the co-movement of the indices showed two regimes.During the fluctuation period,the impulse response of CSI 300 increased by 25% to 50%,CSI 500 responded only when the impulse comes from CSI 300,the impulse response of Growth Enterprises Market Board Index is significantly positive in lagged one period and lagged two period,the impulse response of small and medium-sized board Index increased by 50% to 75%.The results of the study can provide empirical evidence for the policy development and risk management of capital markets.Chapter 4 studies the interdependent structure of the stock index.Based on ARMA-APARCH-HAC model,we estimates the marginal distribution and joint distribution of the four indices of the CSI 300 Index,CSI 500 Index,GEM Composite Index and SME Composite Index.The impact of liquidity shock events on these characteristics is also discussed.My research indicates that During the study period,the inter-market correlation structure described by the hierarchical structure is relatively stable,and the dynamic change of the structure parameters indicates that there are significant differences in the response of different indices to liquidity shock;The first order moments and the multi-order moments of the yield series fluctuate greatly when they are subjected to shock disturbance,the investors vibrated between using the previous information as a positive anchor and a negative anchor;Both the leverage effect and the Taylor effect are enhanced,and the yield has significantly heavier tail during the fluctuation period.Chapter 5 studies the relationship between the expected volatility of GARCHs and the extreme risk under different market conditions.In order to study the relationship between the expected volatility of the GARCH family and its extreme risk in the high market returns of the CSI 300 Index in different market conditions,The VaR measure of systematic financial risk is studied by using the binary extreme method with non-homogeneous rate of overtaking time and yield.The results show that the introduction of the expected volatility corrects the problem that the GPD model is generally degraded in the homogeneous model.The positive effect of the expected volatility on the tail shape parameter is more obvious in the market rising stage than the market decline stage,The higher the expected volatility of the previous period,the smaller the effect of the change of the expected volatility in the next period on VaR.Chapter 6 studies the uncertainty of the threshold and the re-application of the whole sample information.In this chapter,we use the mixed extreme model method,The main distribution within the fitting threshold is fitted by kernel density estimation,the tail distribution outside the fitting threshold is fitted by GPD,the mixed extreme model with continuity constraints at the threshold and the mixed model of two components are analyzed.The results show that the hybrid model can effectively solve the threshold uncertainty problem,in which the non-parametric model based on kernel density estimation is more effective.The kernel bandwidth of the non-parametric model based on kernel density estimation is much smaller than the radius of the mixed region of the parametric compositional mixed model.In the case of poor model fit,the tail risk is slightly over estimated,which meets the prudent regulatory principles.Chapter 7 discusses information and tail dependence.A theoretical model based on information is used to prove that the information acquisition behavior of the subject in order to solve the parameter uncertainty leads to the price jump,which can be described by the extreme value of the return rate and reflects the diffusion path of the uncertainty of the market parameters.The extreme quantile regression method with the re-normalized scale is suitable for statistical analysis of the model hypothesis.The research shows that under the normal market conditions,the uncertainty of the market parameters of CSI 300 are not affected by the uncertainty of the market parameters of the other three stock indexes.However,this independence will be interfered by the resonance between the stock index,uncertainty in market parameters began to spread from the GEM and small plates to the CSI 300.Under the high-frequency data,CSI 500 market parameter uncertainties ease market parameter uncertainties of CSI 300,GEM and SME in boom periods due to arbitrage operation and risk management conducted by investors on the basis of CSI 500.The market parameter uncertainty of SME board and the GEM have similar impact on the market parameter uncertainty of other stock indices.Chapter 8 summarizes the relevant conclusions and offers policy advice,research deficiencies and research perspectives.In this chapter,it is pointed out that in policy-making,it is necessary to pay attention to the penetrating supervision,to form a risk management system with a level and focus,to focus on market operation efficiency,to closely monitor the degree of risk coverage,and to ensure the robustness of the monitoring and monitoring index system of capital market.In the follow-up study,we need to pay more attention to the influence of the microstructure of order structure,new financial technology,cognitive deviation and non-continuous utility,exchange rate and interest rate,corporate performance,industry trend and corporate governance on the risk management of capital market.In this paper,the Chinese stock market is used as an example to study the theoretical causes,structural conditions and extreme features of price volatility in China’s capital markets.The author constructs a theoretical model to explain the formation mechanism of the research object.The characteristics of the research object presented in the theoretical model are measured and analyzed by selecting appropriate measurement tools in different market conditions.The author also tries to build a link between theory and demonstration,and then enhance the feasibility and applicability of the theoretical model.The above work,whether in qualitative research or quantitative research,will help to increase our understanding of capital market structure characteristics,extreme risk management and its dynamic evolution,will help promote better development of the multi-level capital market in depth and breadth,which will help improve the financial supervision system and prevent systemic financial risks.