Price Prediction of Stock Index Futures Based on SVM

Though accurately forecasting the price of stock index futures is impossible, it is of great significance if the price's variation trend can be estimated to a certain extent. In this paper, we adopted a Support Vector Machines method to predict the prices of Stock index futures in the next 5 trading days. First, with an information granulation method, the original data of 3 stock index futures were transformed into a series of fuzzy granules. Then the maximum, medium and minimum values of futures' opening price in each single granule are all extracted. After utilizing the SVM model to regress the values in fuzzy granules, we came up with the variation range of futures' price in the next few days. These predicted results are consistent with the actual one, which proves the feasibility of our method.