The Asset Price Behavior Under The Microstructure Noise

Microstructure noise has been one of the most important research fields in the microstructure theory in recent years. The asset price behavior is affected by microstructure noise affect seriously. The research on this area is necessary and urgent, due to the facts that the specified characteristics of China stock market, the key position of the microstructure noise in the asset price discovery process and the lack of the relevant research on this topic.The dissertation investigates the asset price behavior under the microstructure noise thoroughly with the ultra-high frequency data. The paper consists of four parts: introduction of the whole paper and the microstructure noise (Chapter 1~2); investigation of the characteristics of the microstructure noise and its influencing factors (Chapter 3); investigation of the asset price behavior under microstructure noise (Chapter 4~6); finally, the conclusions and prospects (Chapter 7).The detailed content are as below :(1) Chapter 1 discussed the background, introduction of the problem, and the summary of the relevant research area, also introduced the content, structure and innovation of the dissertation. Chapter 2 contain the introduction of mechanisms of price setting theory, definition of microstructure noise, the difference of the microstructure noise and the noise.(2) Chapter 3 the estimation, properties and the influencing factors of intra-day microstructure noise were researched. The microstructure noise distribution, intraday mode and some other characteristics were investigated. The influencing factors of microstructure noise have been studied from the asymmetric information and liquidity respectively.(3) Chapter 4 the asset pricing model under the microstructure noise. Based on the investigation on the risk properties of microstructure noise, the microstructure noise were introduced in the CAPM as a risk factor, and the model checked empirically. Chapter 5 volatility estimation with microstructure noise bias correction. The daily and higher frequency interval volatility was estimated with TSRV method. The suitability and the robustness of TSRV were checked. The stability and accuracy of the TSRV and RV were compared. Chapter 6 the assets correlation model under the microstructure noise was built. Based on our correlation model the Epps effect were analyzed and the model were checked empirically. (4)Chapter 7 are the conclusions of dissertation, and some prospects of the dissertation are made.