MENN Method Applications for Stock Market Forecasting

Authors:
Guangfeng Jia;Yuehui Chen;Peng Wu
Affiliations:
School of Information Science and Engineering, University of Jinan, Jinan, China 250022;School of Information Science and Engineering, University of Jinan, Jinan, China 250022;School of Information Science and Engineering, University of Jinan, Jinan, China 250022
Venue:
ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks
Year:
2008

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Abstract

A new approach for forecasting stock index based on Multi Expression Neural Network (MENN) is proposed in this paper. The approach employs the multi expression programming (MEP) to evolve the architecture of the MENN and the particle swarm optimization (PSO) to optimize the parameters encoded in the MENN. This framework allows input variables selection, over-layer connections for the various nodes involved. The performance and effectiveness of the proposed method are evaluated using stock market forecasting problems and compared with the related methods.