Predicting FTSE 100 close price using hybrid model

Prediction financial time series (stock index price) is the most challenging task. Support vector regression (SVR), Support vector machine (SVM) and back propagation neural network (BPNN) are the most popular data mining techniques in prediction financial time series. In this paper a hybrid combination model is introduced to combine the three models and to be most beneficial of them all. Quantization factor is used in this paper for the first time to improve the single SVM and SVR prediction output. And also genetic algorithm (GA) used to determine the weights of the proposed model. FTSE100 daily index closing price is used to evaluate the proposed model performance. The proposed hybrid model numerical results shows the outperform result over all other single model and the traditional simple average combiner.

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