Multiple Volatility Estimates Based On High-frequency Financial Data

High frequency financial data to provide richer information from market research in order to present the new darling of the financial sector, while the volatility of the research focus has always been used as an important seat in the financial field. So the question of how to accurately measure fluctuations in capital gains on financial high-profile nature, is one of the core problems in the financial field. Modern financial market conditions changing, rapidly, people need more detailed grasp of the information in response to changes in financial volatility of the market. In the trading and financial markets frequent, low frequency data is not sufficient to fully reflect the true market conditions, will be needed to carry out research on the internal structure of the financial high-frequency data, and computer applications and data availability of high frequency financial data research and development to provide the conditions.In this paper, wavelet transform limited sample of volatility estimation and research related properties, has been achieved by calculating the covariance describes the correlation between samples, and the results are applied to the empirical analysis of multivariate high frequency financial data.