Quantitative Model Construction And Retesting Test Of Stock Index Futures Based On Brin Line

Stock index futures stands for " stock price index futures " refers to the share price index futures contract subject matter of standardization, the two sides agreed on a specific date in the future, may be determined in advance in accordance with the size of the share price index, trading the underlying index. Since February1982Kansas Board of Trade (KCBT) developed the Value Line Composite Index futures contracts since the futures growing importance of various types of investors, trade has expanded rapidly increasing variety of transactions. Currently, the stock index futures have become the world’s largest futures varieties.China Financial Futures Exchange on April16,2010launched the CSI300index futures, marking China’s financial futures markets towards a new stage, a landmark historical significance. CSI300Index compiled by China Securities Index Company, maintain, and publish. The index of300stocks from the Shanghai and Shenzhen exchanges two elected reflects the overall trend of the domestic Shanghai and Shenzhen stock index. Sample selection criteria are the stocks which have the large scale and good mobility. CSI300index sample covers about60%of the market capitalization of the Shanghai and Shenzhen, has a good representative of the market.Our CSI300stock index futures have been running for over three years, during which were active, provides researchers with real and valuable market data. This paper first sort quantitative trading research and the theory of Bollinger, and mathematically prove that the appliance of the theory Bollinger to predict the future is reasonable, then apply Bollinger theoretical to design quantitative trading models based on real data of China’s stock index futures market. The model includes entry rules, add position rules, exits rules and stop loss rules.Select index of the CSI300index futures contract’s main contract minutes April16,2010to June7,2013transaction data back testing trading history. Back testing shows that annual yield reached69.07%of the model, but each year fluctuated greatly benefit ratio, indicating that the model yields good, but the stability should be improved. Finally, this paper put forward the ideas for improving the model to improve profitability and reduce risk, and the suggestions of model using.