Uhf Financial Time Series Modeling And Analysis

In recent years, the analysis of financial ultra high frequency time series has been one of the key and difficult issues in the financial community and research circle. High frequency time series is referred to financial data which is sampled with interval of one hour, one minute even one second. And ultra high frequency time series is tick-by-tick data, which contain plenty of market information. Traditional econometrical modeling is based on fixed interval data. In plenty instances, the econometrical market information is successional and different interval data. Engle and Russell firstly introduced various ACD models for different interval data in 1998.The paper first introduces features of ultra high frequency data and then studies contretely various ACD models. Forecasting ability of several parameterizations of ACD models are compared. We use ACD model to study transaction-by-transaction data of China stock market.Ultra high frequency time series contains two variables in generally: one is the time of the business advent, another is the marks including price of exchange, sale volume etc. Ghysels and Jasiak combined ACD and ARCH models which comed into ACD-GARCH model for reflecting important information of two variables. Variety of the exchange gross reflects important information of about market exchange. So intensive study has great effect on bargainer's behavior and the microcosmic structure market of the stock exchange. So on the base of the study results of former in this field, this paper constructes the ACD-GARCH-S model through joining exchange gross variety in the former model. Then we use the model to analysis the relationship among the transactions duration , ultra-high-frequency exchange gross variety and the returns , variances for the index of Shanghai stock market.At last, the paper reviews the research of this paper and points out its'research trend.