Using Chaotic Neural Network to Forecast Stock Index

Authors:
Bo Ning;Jiutao Wu;Hui Peng;Jianye Zhao
Affiliations:
School of Electronics Engineering and Computer Science, Peking University, Beijing, China 100871;School of Electronics Engineering and Computer Science, Peking University, Beijing, China 100871;School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing, China 100876;School of Electronics Engineering and Computer Science, Peking University, Beijing, China 100871
Venue:
ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
Year:
2009

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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.