| There is a huge fluctuation in China’s stock market since 2015. The reason of this phenomenon vary from the imperfect trading mechanism to the less risk awareness investors. In addition, it’s another reason that government regulators departments and media can not warn the potential risk and disclose information to the public accurately and timely. In order to reduce part of the price risk taken by the investor, maintain the stability of financial market and improve people’s confidence, the market regulators need to establish effective rules and regulations to improve the relevant departments’ability to predict the risk in the stock market. Important information of the stock market reflected by Duration between transactions in the process of asset price formation will have different influence on traders’behavior, which will lead to the volatility of financial asset price. The fluctuation of financial asset is often used to measure the risk of financial market. So investors can judge the size of asset price fluctuation by the information contained in duration and regulators can predict the market risk effectively. This paper conduct an empirical analysis with duration and volatility which are two essential factors in the process of price formation as studying objectives, analyzing the impact of the information provided by the market itself on the price formation and fluctuation.As for the measure of duration and volatility, traditional economics is based on low frequency and constant duration. But most of the information in financial markets is a continuous change process with unequal duration. So this paper adopt high-frequency data collected per hour, every minute, or even every second. Compared with the low frequency data, high frequency data contains more abundant market information, which make the research of this paper more scientific and practical.First of all, this paper introduces the basic content of microstructure of financial market and price formation theory, three important hypotheses of information model, the definition of volatility to illuminate the process of price formation process and its operation mechanism. three hypotheses hold different point of view on the relationship between duration and volatility of return and the subsequent empirical analysis will test it. Then, this paper introduces the characteristics of high frequency time series and the type of ACD model. The ACD model is mainly used to simulate the duration between transactions. The modeling idea is based on past events, and the purpose of this model with unequal duration is to analyze the conditional distribution of the duration. Secondly, The test of Ping an Group’s high-frequency data turns out that there is a conspicuous "calendar effect" showing U-shape in duration series. In order to choose a proper ACD model which is suitable for china’s stock market, this paper conduct an empirical analysis for the EACD, WACD model and GACD model. In the model of UHF-GARCH-M another variable volume change rate is introduced to the model UHF-GARCH. Through the empirical analysis we investigates the relationship between duration and the return and volatility when anther variable is added. Finally, the paper reviews the research of this paper and points out its’ research trend.By the analysis of this paper, the author gets the conclusions as the follows:(1) The duration series have "calendar effect", and showing U-shape.(2)The duration series have clustering characteristic and persistence effect. EACD model is more suitable for the duration of china’s stock market.(3)The relationship of duration and volatility is positive when joining another variable in the former model. This support the hypothesis of Easley and O’Hara that on transaction means no news.In summary, the use of high frequency data made the research of risk control more scientific and practical. The result of this paper have a certain reference value for the transaction, supervision and the actual investment operation of the investor and investment institutions. |
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