The Analysis Of Second-order Volatility Matrix Under High Frequency Financial Data

In finance field, uncertain risk, the volatility of assets returns process, is the origin of chasing benefits in the market, Assets returns process affected by many factors in market environment is objectively forming the uncertain fluctuation. Whatever for chasing benefits or assets value-keeping purpose people always hope being able to forecast the best results to the upcoming fluctuation. Relying on advanced computer and data storing technology it is more and easier to gain high frequency finance data. People hopes make the much better forecasting to volatility by the high frequency finance data that is depicted more exquisite to market details.Under the continuous diffusion price model of signal asset, Lan Zhang & Myland etc invented two-time scale and multiple-time scale. As market returns frequently contain jumps, it is important to have methods that handle automatically the possible jumps in the financial market. This paper propose several kinds of the estimation methods of market mircrostruture noise error under different assumptions and also propose the estimation of realized Volatility matrix under jump-diffusion price processes of two assets. First of all, we propose several kinds of the estimation method of market microstructure noise error under different assumptions and deeply test between them and old ones. We also derive its asymptotic properties. And later, in the volatility study field, the effect of the market microstructure noise and jumps on the high frequency finance data have appeared .Based on single asset jump-diffusion of pricing processes, handling data with jumps and microstructure noise separately. We obtained the estimations of second-order jump covariance matrix and second-order volatility matrix under jump-diffusion price processes of two assets and them convergence rate.