The Empirical Trading Strategy Research Of The HS300 Share Index Future Based On The Autoregressive Conditional Duration Model

The year 2015 will be the age of hedge fund because many hedging intruments emerge into our sight. And in China, more and more institutional investors will adopt the quantitative investment method to research lots of trading varieties such as HS300 stock index futures and so on.In the research field of market microstructure, autoregressive conditional duration model is gradually researched by multitudes of scholars. In their empirical research, the autoregressive conditional duration model has some certain effect in enclosing the law of the market information. In this paper, I also test how t-he autoregressive conditional duration model can be used in the field of share price index futures, whose final empirical result indicates that there is information asymmetry in the share price index futures market. Consequently, we are able to design the future trading strategy on the basis of the empirical results.In this paper, I design two share price index futures trading strategies by using the data of share price index futures in different time level. The one is the statistical arbitrage trading strategy which becomes mature in China. The other one is the trading strategy based on the information revealed by the auto-regressive conditional duration model. Empirical results indicates that the statistical arbitrage strategy will behave best on the one minute level with the 4.49 profit-risk ratio while the autoregressive conditional duration model strategy behaves best on the tick data level with 4.28 profit-risk ratio. So compared to the statistical arbitrage strategy, we deem that the autoregressive conditional model can be used to design the share price index futures trading strategy if the market is always around with the frequent band.