Abstract
In this paper, a new scheme based on chaotic neural network for stock index prediction is proposed. The data from a Chinese stock market, Shenzhen stock market, are applied as a case study. The chaotic neural network is used to learn the non-linear stochastic and chaotic patterns in the stock system and forecast a new index with former indexes. The validity of the scheme is analyzed theoretically, and the simulation results show that it has a good performance. © 2009 Springer Berlin Heidelberg.
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CITATION STYLE
Ning, B., Wu, J., Peng, H., & Zhao, J. (2009). Using chaotic neural network to forecast stock index. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5551 LNCS, pp. 870–876). https://doi.org/10.1007/978-3-642-01507-6_98
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