Abstract-Prediction stock price is considered the most challenging and important financial topic. Thus, its complexity, nonlinearity and much other characteristic, single method could not optimize a good result. Hence, this paper proposes a hybrid ensemble model based on BP neural network and EEMD to predict FTSE100 closing price. In this paper there are five hybrid prediction models, EEMD-NN, EEMD-Bagging-NN, EEMD-Cross validation-NN, EEMD-CV-Bagging-NN and EEMD-NN-Proposed method. Experimental result shows that EEMD-Bagging-NN, EEMD-Cross validation-NN and EEMD-CV-Bagging-NN models performance are a notch above EEMD-NN and significantly higher than the single-NN model. In addition, EEMD-NN-Proposed method prediction performance superiority is demonstrated comparing with the all presented model in this paper, and was feasible and effective in prediction FTSE100 closing price. As a result of the significant performance of the proposed method, the method can be utilized to predict other financial time series data.
Reference REF proposes a hybrid ensemble model based on BP neural network and EEMD to predict FTSE100 closing price.
A novel hybrid ensemble model to predict FTSE100 index by combining neural network and EEMD
2015 European Control Conference (ECC)
2015 European Control Conference (ECC)
Engineering Computer Science