Research on the modelling of realized volatility based on multivariate high-frequency data

High-frequency financial data analysis and modeling are a new research field in financial econometrics.The paper extends realized volatility based on high-frequency data to realized covariance matrix based on multivariate highfrequency data,to describe volatility and correlation of multivariate.Then the paper studies the characteristics of the realized covariance matrix of Shanghai Composite Index and Shenzhen Component Index,and constructs FIVAR model to its' long memory characteristic,to describe their volatility and correlation.The research shows that the realized volatility and the realized covariance after taking logarithm have good normal distribution characteristics and the same long memory characteristics.The FIVAR model based on realized covariance matrix is good basis of studying co-persistence.