| With the stock index futures market investors increasing and trading volume enlarging, its impact on the stock market becomes more deepen. In this thesis, according to the technical analys is method of futures market and classification model of LVQ neural network, we select the Shanghai and Shenzhen 300 Index Futures(IF) and the CSI 500 Stock Index Futures(IC) day market information as input vector and the stock index future trend as the output vector. In the view of technical analysis, the variables that affect the trend of stock index in stock index futures day market information are selected. Then the stock index futures contract is classified by "time", the thesis studies the influence of the "price", "quant ity" and "t ime" of the futures market on the future trend of the stock index. Through the input vectors are in the form of price category or volume, trading volume and other forms of combination, then we choose stock index futures contracts with different time of listing, which could help study the influence of the "price", "quant ity" and "t ime" of the futures market on the future trend of the stock index. We will discover the trend of the stock index by the interaction of the quantity and price category of the futures market. Overall the sensitivity of the price and quantity category is different. Specifically, IC futures contracts for the various continuous index and IF quarter month futures contract quantity category variable identify index rosing correct rate high, IF continuous and continuous next season, the amount of categories of factors on the stock index fail to ident ify the correct rate of high, IF next month for the continuous price category and the amount of categories of factors that can ident ify the stock index rose or fell. However, the price and quantity category of IF futures continuous contracts are no sensitive to the trend of stock index. The above results can help investors to judge the trend of the stock market. |
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