Prediction of the Price of Stock Index Futures Based on SVM and Triangular Fuzzy Information Granulation Concerning Investors Sentiment

Yan LIN, Jianhui YANG


This paper proposed a hybrid model based on triangular fuzzy information granulation and SVM to predict the trend and fluctuation range of the price of stock index futures. Firstly, the original data is processed by triangular fuzzy information granulation. Then, the cross validation method is used to obtain the parameters of SVM. Also some significant factors concerning investors sentiment are considered to improve the forecast accuracy of the hybrid model. At last, the hybrid model is used to perform empirically study based on HS300 stock index futures data after fuzzy information granulation. The empirical analysis showed that the hybrid model owns the better preformation for the prediction of the change trend and range of the price of stock index futures. After concerning investors sentiment, the accuracy of prediction is also improved effectively.


Stock index future; Fuzzy information granulation; Support Vector Machine (SVM); Investors sentiment

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