The Influnence Analysis Of Financial Volatility Based On High-frequency Data

Before 1990s,what we can study and explore in financial economic and time series only just on the day,week,month,and even year's reported data with restriction of the market prosperity and science technology.The update of this data is low which is called low-frequency data.Along with rapid development of economic,people can obtain the more high-er frequency data,and by the modern computer it is possible to storage the data cheaply.Especially in recent years,because of the revolution in communication and network technology,people can easily capture the real-time trading data in financial market,and the data can be in seconds or less interval time.To model and analysis the high frequency and ultra high frequency data which has important significance both in financial engineering and financial metrology.To make profit is heading with risk in the financial markets.The volatility of profiting is a good indicator of it.To be the benefit maximization and assets hedge, people hope to make description of the details of the financial markets,which based on calculate the realized volatility to predict the upcoming volatility, so we focus on the estimate of the volatility in the study of the high frequency financial data.The key points and main achievements are listed as follows:1. Using the TSRV integral volatility calculation method, we discuss the con-vergence and divergence of three?four time variation with market microstructure noise.2.Hypothesis testing method is used to contrast experiment, we present the time endogenous in real financial data.