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Title: A novel hybrid ensemble model to predict FTSE100 index by combining neural network and EEMD
Authors: Al-Hnaity, B
Abbod, M
Keywords: Artificial neural network;Hybrid ensemble model;BP;EEMD;FTSE100
Issue Date: 2015
Publisher: IEEE
Citation: 2015 European Control Conference, ECC 2015, pp. 3021 - 3028, Linz, Austria, (15 -17 July 2015)
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.
ISBN: 9783952426937
Appears in Collections:Dept of Electronic and Computer Engineering Research Papers

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